etymology of hypothesis

• 1.1 Etymology
• 1.2 Pronunciation
• 1.3.1 Synonyms
• 1.3.2 Derived terms
• 1.3.3 Translations
• 2.1 Etymology
• 2.2 Pronunciation
• 2.3.1 Declension

Recorded since 1596, from Middle French hypothese , from Late Latin hypothesis , from Ancient Greek ὑπόθεσις ( hupóthesis , “ base, basis of an argument, supposition ” , literally “ a placing under ” ) , itself from ὑποτίθημι ( hupotíthēmi , “ I set before, suggest ” ) , from ὑπό ( hupó , “ below ” ) + τίθημι ( títhēmi , “ I put, place ” ) .

Pronunciation

• ( UK ) IPA ( key ) : /haɪˈpɒθɪsɪs/ , /hɪˈpɒθɪsɪs/ , /həˈpɒθɪsɪs/ , /-əsəs/ , /-əsɪs/
• ( US ) IPA ( key ) : /haɪˈpɑː.θə.sɪs/

hypothesis ( plural hypotheses )

• 2001 September 27, Terrie E. Moffitt, Avshalom Caspi, Michael Rutter, Phil A. Silva, Sex Differences in Antisocial Behaviour: Conduct Disorder, Delinquency, and Violence in the Dunedin Longitudinal Study ‎ [1] , Cambridge University Press , →ISBN , page 151 : This hypothesis goes by many names, including group resistence, the threshold effect, and the gender paradox. Because the hypothesis holds such wide appeal, it is worth revisiting the logic behind it. The hypothesis is built on the factual observation that fewer females than males act antisocially.
• 2005 , Ronald H. Pine, http://www.csicop.org/specialarticles/show/intelligent_design_or_no_model_creationism , 15 October 2005: Far too many of us have been taught in school that a scientist, in the course of trying to figure something out, will first come up with a " hypothesis " (a guess or surmise—not necessarily even an "educated" guess). ... [But t]he word " hypothesis " should be used, in science, exclusively for a reasoned, sensible, knowledge-informed explanation for why some phenomenon exists or occurs. An hypothesis can be as yet untested; can have already been tested; may have been falsified; may have not yet been falsified, although tested; or may have been tested in a myriad of ways countless times without being falsified; and it may come to be universally accepted by the scientific community. An understanding of the word " hypothesis ," as used in science, requires a grasp of the principles underlying Occam's Razor and Karl Popper's thought in regard to " falsifiability "—including the notion that any respectable scientific hypothesis must, in principle, be "capable of" being proven wrong (if it should, in fact, just happen to be wrong), but none can ever be proved to be true. One aspect of a proper understanding of the word " hypothesis ," as used in science, is that only a vanishingly small percentage of hypotheses could ever potentially become a theory.
• ( general ) An assumption taken to be true for the purpose of argument or investigation .
• ( grammar ) The antecedent of a conditional statement .
• supposition
• educated guess
• See also Thesaurus:supposition

Derived terms

• alternative hypothesis
• aquatic ape hypothesis
• Avogadro's hypothesis
• conspiracy hypothesis
• continuum hypothesis
• cosmic censorship hypothesis
• documentary hypothesis
• efficient market hypothesis
• ergodic hypothesis
• expectations hypothesis
• Fisher hypothesis
• Gaia hypothesis
• generalized continuum hypothesis
• God hypothesis
• Griesbach hypothesis
• hypothesize
• hypothetical
• hypothetically
• interface hypothesis
• just-world hypothesis
• level-ordering hypothesis
• mafia hypothesis
• Medea hypothesis
• Monro-Kellie hypothesis
• null hypothesis
• Omphalos hypothesis
• Out of India hypothesis
• ovulatory shift hypothesis
• permanent income hypothesis
• Prout's hypothesis
• Rare Earth hypothesis
• Red Queen hypothesis
• Riemann hypothesis
• Sapir-Whorf hypothesis
• Schinzel's hypothesis H
• sexy son hypothesis
• simulation hypothesis
• swoon hypothesis
• trickle-down hypothesis
• trickle down hypothesis
• Wellhausen's hypothesis
• working hypothesis
• zombie hypothesis

Translations

Borrowed from Ancient Greek ὑπόθεσις ( hupóthesis , “ hypothesis ” , noun ) .

• ( Classical Latin ) IPA ( key ) : /hyˈpo.tʰe.sis/ , [hʏˈpɔt̪ʰɛs̠ɪs̠]
• ( modern Italianate Ecclesiastical ) IPA ( key ) : /iˈpo.te.sis/ , [iˈpɔːt̪es̬is]

hypothesis   f ( genitive hypothesis or hypotheseōs or hypothesios ) ; third declension

1 Found sometimes in Medieval and New Latin.

• There is also genitive plural hypotheseōn .
• The genitive singular is also spelled hypotheseωs and the genitive plural hypotheseωn .

• English terms derived from Proto-Indo-European
• English terms derived from the Proto-Indo-European root *dʰeh₁-
• English terms borrowed from Middle French
• English terms derived from Middle French
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Definition of hypothesis

Did you know.

The Difference Between Hypothesis and Theory

A hypothesis is an assumption, an idea that is proposed for the sake of argument so that it can be tested to see if it might be true.

In the scientific method, the hypothesis is constructed before any applicable research has been done, apart from a basic background review. You ask a question, read up on what has been studied before, and then form a hypothesis.

A hypothesis is usually tentative; it's an assumption or suggestion made strictly for the objective of being tested.

A theory , in contrast, is a principle that has been formed as an attempt to explain things that have already been substantiated by data. It is used in the names of a number of principles accepted in the scientific community, such as the Big Bang Theory . Because of the rigors of experimentation and control, it is understood to be more likely to be true than a hypothesis is.

In non-scientific use, however, hypothesis and theory are often used interchangeably to mean simply an idea, speculation, or hunch, with theory being the more common choice.

Since this casual use does away with the distinctions upheld by the scientific community, hypothesis and theory are prone to being wrongly interpreted even when they are encountered in scientific contexts—or at least, contexts that allude to scientific study without making the critical distinction that scientists employ when weighing hypotheses and theories.

The most common occurrence is when theory is interpreted—and sometimes even gleefully seized upon—to mean something having less truth value than other scientific principles. (The word law applies to principles so firmly established that they are almost never questioned, such as the law of gravity.)

This mistake is one of projection: since we use theory in general to mean something lightly speculated, then it's implied that scientists must be talking about the same level of uncertainty when they use theory to refer to their well-tested and reasoned principles.

The distinction has come to the forefront particularly on occasions when the content of science curricula in schools has been challenged—notably, when a school board in Georgia put stickers on textbooks stating that evolution was "a theory, not a fact, regarding the origin of living things." As Kenneth R. Miller, a cell biologist at Brown University, has said , a theory "doesn’t mean a hunch or a guess. A theory is a system of explanations that ties together a whole bunch of facts. It not only explains those facts, but predicts what you ought to find from other observations and experiments.”

While theories are never completely infallible, they form the basis of scientific reasoning because, as Miller said "to the best of our ability, we’ve tested them, and they’ve held up."

• proposition
• supposition

hypothesis , theory , law mean a formula derived by inference from scientific data that explains a principle operating in nature.

hypothesis implies insufficient evidence to provide more than a tentative explanation.

theory implies a greater range of evidence and greater likelihood of truth.

law implies a statement of order and relation in nature that has been found to be invariable under the same conditions.

Examples of hypothesis in a Sentence

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'hypothesis.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

Greek, from hypotithenai to put under, suppose, from hypo- + tithenai to put — more at do

1641, in the meaning defined at sense 1a

Phrases Containing hypothesis

• counter - hypothesis
• nebular hypothesis
• null hypothesis
• planetesimal hypothesis
• Whorfian hypothesis

Articles Related to hypothesis

This is the Difference Between a...

This is the Difference Between a Hypothesis and a Theory

In scientific reasoning, they're two completely different things

Dictionary Entries Near hypothesis

hypothermia

hypothesize

Cite this Entry

“Hypothesis.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/hypothesis. Accessed 26 Jun. 2024.

Kids Definition

Kids definition of hypothesis, medical definition, medical definition of hypothesis, more from merriam-webster on hypothesis.

Nglish: Translation of hypothesis for Spanish Speakers

Britannica English: Translation of hypothesis for Arabic Speakers

Britannica.com: Encyclopedia article about hypothesis

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• Education Resources Information Center - Understanding Hypotheses, Predictions, Laws, and Theories
• Simply Psychology - Research Hypothesis: Definition, Types, & Examples
• Cornell University - The Learning Strategies Center - Hypothesis
• Washington State University - Developing a Hypothesis
• Verywell Mind - Forming a Good Hypothesis for Scientific Research
• BCCampus Publishing - Research Methods for the Social Sciences: An Introduction - Hypotheses

hypothesis , something supposed or taken for granted, with the object of following out its consequences (Greek hypothesis , “a putting under,” the Latin equivalent being suppositio ).

In planning a course of action, one may consider various alternatives , working out each in detail. Although the word hypothesis is not typically used in this case, the procedure is virtually the same as that of an investigator of crime considering various suspects. Different methods may be used for deciding what the various alternatives may be, but what is fundamental is the consideration of a supposal as if it were true, without actually accepting it as true. One of the earliest uses of the word in this sense was in geometry . It is described by Plato in the Meno .

The most important modern use of a hypothesis is in relation to scientific investigation . A scientist is not merely concerned to accumulate such facts as can be discovered by observation: linkages must be discovered to connect those facts. An initial puzzle or problem provides the impetus , but clues must be used to ascertain which facts will help yield a solution. The best guide is a tentative hypothesis, which fits within the existing body of doctrine. It is so framed that, with its help, deductions can be made that under certain factual conditions (“initial conditions”) certain other facts would be found if the hypothesis were correct.

The concepts involved in the hypothesis need not themselves refer to observable objects. However, the initial conditions should be able to be observed or to be produced experimentally, and the deduced facts should be able to be observed. William Harvey ’s research on circulation in animals demonstrates how greatly experimental observation can be helped by a fruitful hypothesis. While a hypothesis can be partially confirmed by showing that what is deduced from it with certain initial conditions is actually found under those conditions, it cannot be completely proved in this way. What would have to be shown is that no other hypothesis would serve. Hence, in assessing the soundness of a hypothesis, stress is laid on the range and variety of facts that can be brought under its scope. Again, it is important that it should be capable of being linked systematically with hypotheses which have been found fertile in other fields.

If the predictions derived from the hypothesis are not found to be true, the hypothesis may have to be given up or modified. The fault may lie, however, in some other principle forming part of the body of accepted doctrine which has been utilized in deducing consequences from the hypothesis. It may also lie in the fact that other conditions, hitherto unobserved, are present beside the initial conditions, affecting the result. Thus the hypothesis may be kept, pending further examination of facts or some remodeling of principles. A good illustration of this is to be found in the history of the corpuscular and the undulatory hypotheses about light .

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Dictionary definition of hypothesis

An educated guess or a proposed explanation for a phenomenon or a pattern of observations. "The experiment yielded results that supported the initial hypothesis ."

Detailed meaning of hypothesis

It is a statement that can be tested through scientific experimentation or further observation. In scientific research, a hypothesis is used as a starting point for an investigation, and it serves as a basis for designing experiments and collecting data to either support or disprove it. A hypothesis typically consists of two parts: the independent variable, which is the factor being tested, and the dependent variable, which is the effect that is being observed. The hypothesis states the expected relationship between the two variables. For example, if a scientist wants to test the effect of a new drug on blood pressure, the independent variable would be the drug and the dependent variable would be the blood pressure. The hypothesis in this case would be "The new drug will lower blood pressure" A hypothesis is a crucial step in the scientific method as it guides the research and helps to focus on a specific question or problem. The results of the research and experimentation can support or disprove the hypothesis , and it can lead to new discoveries and knowledge. In summary, a hypothesis is an educated guess or proposed explanation for a phenomenon or a pattern of observations, it's a statement that can be tested through scientific experimentation or further observation, it's a crucial step in the scientific method that guides the research and helps to focus on a specific question or problem.

Example sentences containing hypothesis

1. The scientist formulated a hypothesis to explain the observed phenomenon. 2. The hypothesis proposed by the researcher challenged the existing theories in the field. 3. The students conducted experiments to test their hypothesis about plant growth. 4. The hypothesis stated that increased exposure to sunlight would improve mood. 5. The team developed a hypothesis to investigate the effects of a new drug on cancer cells. 6. The hypothesis suggested that regular exercise would lead to improved cognitive function.

History and etymology of hypothesis

The noun ' hypothesis ' draws its linguistic lineage from the combination of two ancient Greek elements. The first part, 'hypo,' originates from the Greek word 'hupo,' meaning 'under' or 'beneath.' The second component, 'thesis,' derives from 'tithēmi,' meaning 'to place' or 'to put forth.' In the context of scientific inquiry and philosophical discourse, the term ' hypothesis ' embodies the notion of putting forth an educated guess or proposition that lies beneath the surface of empirical observation. It signifies a preliminary and testable explanation for a phenomenon or a pattern of observations. Thus, the etymology of ' hypothesis ' underscores its foundational role in the systematic process of scientific inquiry, where ideas are posited as a starting point for further investigation and analysis.

Quiz: Find the meaning of hypothesis

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Further usage examples of hypothesis

1. The scientist's hypothesis about the origins of the universe sparked a lively debate among colleagues. 2. The study aimed to confirm or refute the hypothesis that caffeine enhances athletic performance. 3. The researchers gathered data to support their hypothesis on the relationship between sleep and memory. 4. The hypothesis proposed that increased levels of pollution would lead to a decline in air quality. 5. The hypothesis suggested that exposure to violent media would lead to increased aggression in children. 6. The scientists revised their hypothesis based on the new evidence they gathered. 7. The study failed to confirm the hypothesis , leading the researchers to reconsider their approach. 8. The hypothesis provided a framework for the investigation, guiding the research process. 9. The scientist presented a compelling hypothesis that challenged conventional wisdom. 10. The hypothesis proposed that higher levels of stress would negatively affect decision-making abilities. 11. The researcher's hypothesis about the effects of music on productivity generated significant interest. 12. The study aimed to test the hypothesis that a specific diet would improve cardiovascular health. 13. The scientist formulated a hypothesis to test in the laboratory. 14. Her hypothesis about the market trends proved accurate. 15. We need evidence to support or refute this hypothesis . 16. The hypothesis was the starting point for the research project. 17. The hypothesis suggests a link between two variables. 18. He proposed an intriguing hypothesis for the mysterious phenomenon. 19. The hypothesis was based on years of careful observation. 20. The team's hypothesis challenged established scientific beliefs. 21. To validate the hypothesis , experiments were meticulously designed. 22. The hypothesis explained the unexpected results of the study. 23. Researchers are now testing the hypothesis with real-world data. 24. The success of the mission hinged on the accuracy of the initial hypothesis .

Quiz categories containing hypothesis

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hunch,proposal

eb68db_80f17f7a153340fd98f74a39f7c06f32.mp3

theory, fact, certainty, knowledge

https://static.wixstatic.com/media/eb68db_7deb1bd10b274eeca38fe2f821b50c0d~mv2.jpg, https://static.wixstatic.com/media/eb68db_14656208e4464bb1a273d7ac7b8c2c94~mv2.jpg, https://static.wixstatic.com/media/eb68db_8aaddd85f1ff405b94e083dd525eb61f~mv2.jpg, https://static.wixstatic.com/media/eb68db_8aaddd85f1ff405b94e083dd525eb61f~mv2.jpg

conjecture,postulate,premise,proposition,suggestion,supposition,thesis

TOEFL 5, Analytical and Interpretive, Inquiry and Insight, Insight and Intelligence

Hypothesis n., plural: hypotheses [/haɪˈpɑːθəsɪs/] Definition: Testable scientific prediction

Table of Contents

What Is Hypothesis?

A scientific hypothesis is a foundational element of the scientific method . It’s a testable statement proposing a potential explanation for natural phenomena. The term hypothesis means “little theory” . A hypothesis is a short statement that can be tested and gives a possible reason for a phenomenon or a possible link between two variables . In the setting of scientific research, a hypothesis is a tentative explanation or statement that can be proven wrong and is used to guide experiments and empirical research.

It is an important part of the scientific method because it gives a basis for planning tests, gathering data, and judging evidence to see if it is true and could help us understand how natural things work. Several hypotheses can be tested in the real world, and the results of careful and systematic observation and analysis can be used to support, reject, or improve them.

Researchers and scientists often use the word hypothesis to refer to this educated guess . These hypotheses are firmly established based on scientific principles and the rigorous testing of new technology and experiments .

For example, in astrophysics, the Big Bang Theory is a working hypothesis that explains the origins of the universe and considers it as a natural phenomenon. It is among the most prominent scientific hypotheses in the field.

“The scientific method: steps, terms, and examples” by Scishow:

Biology definition: A hypothesis  is a supposition or tentative explanation for (a group of) phenomena, (a set of) facts, or a scientific inquiry that may be tested, verified or answered by further investigation or methodological experiment. It is like a scientific guess . It’s an idea or prediction that scientists make before they do experiments. They use it to guess what might happen and then test it to see if they were right. It’s like a smart guess that helps them learn new things. A scientific hypothesis that has been verified through scientific experiment and research may well be considered a scientific theory .

Etymology: The word “hypothesis” comes from the Greek word “hupothesis,” which means “a basis” or “a supposition.” It combines “hupo” (under) and “thesis” (placing). Synonym:   proposition; assumption; conjecture; postulate Compare:   theory See also: null hypothesis

Characteristics Of Hypothesis

A useful hypothesis must have the following qualities:

• It should never be written as a question.
• You should be able to test it in the real world to see if it’s right or wrong.
• It needs to be clear and exact.
• It should list the factors that will be used to figure out the relationship.
• It should only talk about one thing. You can make a theory in either a descriptive or form of relationship.
• It shouldn’t go against any natural rule that everyone knows is true. Verification will be done well with the tools and methods that are available.
• It should be written in as simple a way as possible so that everyone can understand it.
• It must explain what happened to make an answer necessary.
• It should be testable in a fair amount of time.
• It shouldn’t say different things.

Sources Of Hypothesis

Sources of hypothesis are:

• Patterns of similarity between the phenomenon under investigation and existing hypotheses.
• Insights derived from prior research, concurrent observations, and insights from opposing perspectives.
• The formulations are derived from accepted scientific theories and proposed by researchers.
• In research, it’s essential to consider hypothesis as different subject areas may require various hypotheses (plural form of hypothesis). Researchers also establish a significance level to determine the strength of evidence supporting a hypothesis.
• Individual cognitive processes also contribute to the formation of hypotheses.

One hypothesis is a tentative explanation for an observation or phenomenon. It is based on prior knowledge and understanding of the world, and it can be tested by gathering and analyzing data. Observed facts are the data that are collected to test a hypothesis. They can support or refute the hypothesis.

For example, the hypothesis that “eating more fruits and vegetables will improve your health” can be tested by gathering data on the health of people who eat different amounts of fruits and vegetables. If the people who eat more fruits and vegetables are healthier than those who eat less fruits and vegetables, then the hypothesis is supported.

Hypotheses are essential for scientific inquiry. They help scientists to focus their research, to design experiments, and to interpret their results. They are also essential for the development of scientific theories.

Types Of Hypothesis

In research, you typically encounter two types of hypothesis: the alternative hypothesis (which proposes a relationship between variables) and the null hypothesis (which suggests no relationship).

Simple Hypothesis

It illustrates the association between one dependent variable and one independent variable. For instance, if you consume more vegetables, you will lose weight more quickly. Here, increasing vegetable consumption is the independent variable, while weight loss is the dependent variable.

Complex Hypothesis

It exhibits the relationship between at least two dependent variables and at least two independent variables. Eating more vegetables and fruits results in weight loss, radiant skin, and a decreased risk of numerous diseases, including heart disease.

Directional Hypothesis

It shows that a researcher wants to reach a certain goal. The way the factors are related can also tell us about their nature. For example, four-year-old children who eat well over a time of five years have a higher IQ than children who don’t eat well. This shows what happened and how it happened.

Non-directional Hypothesis

When there is no theory involved, it is used. It is a statement that there is a connection between two variables, but it doesn’t say what that relationship is or which way it goes.

Null Hypothesis

It says something that goes against the theory. It’s a statement that says something is not true, and there is no link between the independent and dependent factors. “H 0 ” represents the null hypothesis.

Associative and Causal Hypothesis

When a change in one variable causes a change in the other variable, this is called the associative hypothesis . The causal hypothesis, on the other hand, says that there is a cause-and-effect relationship between two or more factors.

Examples Of Hypothesis

Examples of simple hypotheses:

• Students who consume breakfast before taking a math test will have a better overall performance than students who do not consume breakfast.
• Students who experience test anxiety before an English examination will get lower scores than students who do not experience test anxiety.
• Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone, is a statement that suggests that drivers who talk on the phone while driving are more likely to make mistakes.

Examples of a complex hypothesis:

• Individuals who consume a lot of sugar and don’t get much exercise are at an increased risk of developing depression.
• Younger people who are routinely exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces, according to a new study.
• Increased levels of air pollution led to higher rates of respiratory illnesses, which in turn resulted in increased costs for healthcare for the affected communities.

Examples of Directional Hypothesis:

• The crop yield will go up a lot if the amount of fertilizer is increased.
• Patients who have surgery and are exposed to more stress will need more time to get better.
• Increasing the frequency of brand advertising on social media will lead to a significant increase in brand awareness among the target audience.

Examples of Non-Directional Hypothesis (or Two-Tailed Hypothesis):

• The test scores of two groups of students are very different from each other.
• There is a link between gender and being happy at work.
• There is a correlation between the amount of caffeine an individual consumes and the speed with which they react.

Examples of a null hypothesis:

• Children who receive a new reading intervention will have scores that are different than students who do not receive the intervention.
• The results of a memory recall test will not reveal any significant gap in performance between children and adults.
• There is not a significant relationship between the number of hours spent playing video games and academic performance.

Examples of Associative Hypothesis:

• There is a link between how many hours you spend studying and how well you do in school.
• Drinking sugary drinks is bad for your health as a whole.
• There is an association between socioeconomic status and access to quality healthcare services in urban neighborhoods.

Functions Of Hypothesis

The research issue can be understood better with the help of a hypothesis, which is why developing one is crucial. The following are some of the specific roles that a hypothesis plays: (Rashid, Apr 20, 2022)

• A hypothesis gives a study a point of concentration. It enlightens us as to the specific characteristics of a study subject we need to look into.
• It instructs us on what data to acquire as well as what data we should not collect, giving the study a focal point .
• The development of a hypothesis improves objectivity since it enables the establishment of a focal point.
• A hypothesis makes it possible for us to contribute to the development of the theory. Because of this, we are in a position to definitively determine what is true and what is untrue .

How will Hypothesis help in the Scientific Method?

• The scientific method begins with observation and inquiry about the natural world when formulating research questions. Researchers can refine their observations and queries into specific, testable research questions with the aid of hypothesis. They provide an investigation with a focused starting point.
• Hypothesis generate specific predictions regarding the expected outcomes of experiments or observations. These forecasts are founded on the researcher’s current knowledge of the subject. They elucidate what researchers anticipate observing if the hypothesis is true.
• Hypothesis direct the design of experiments and data collection techniques. Researchers can use them to determine which variables to measure or manipulate, which data to obtain, and how to conduct systematic and controlled research.
• Following the formulation of a hypothesis and the design of an experiment, researchers collect data through observation, measurement, or experimentation. The collected data is used to verify the hypothesis’s predictions.
• Hypothesis establish the criteria for evaluating experiment results. The observed data are compared to the predictions generated by the hypothesis. This analysis helps determine whether empirical evidence supports or refutes the hypothesis.
• The results of experiments or observations are used to derive conclusions regarding the hypothesis. If the data support the predictions, then the hypothesis is supported. If this is not the case, the hypothesis may be revised or rejected, leading to the formulation of new queries and hypothesis.
• The scientific approach is iterative, resulting in new hypothesis and research issues from previous trials. This cycle of hypothesis generation, testing, and refining drives scientific progress.

Importance Of Hypothesis

• Hypothesis are testable statements that enable scientists to determine if their predictions are accurate. This assessment is essential to the scientific method, which is based on empirical evidence.
• Hypothesis serve as the foundation for designing experiments or data collection techniques. They can be used by researchers to develop protocols and procedures that will produce meaningful results.
• Hypothesis hold scientists accountable for their assertions. They establish expectations for what the research should reveal and enable others to assess the validity of the findings.
• Hypothesis aid in identifying the most important variables of a study. The variables can then be measured, manipulated, or analyzed to determine their relationships.
• Hypothesis assist researchers in allocating their resources efficiently. They ensure that time, money, and effort are spent investigating specific concerns, as opposed to exploring random concepts.
• Testing hypothesis contribute to the scientific body of knowledge. Whether or not a hypothesis is supported, the results contribute to our understanding of a phenomenon.
• Hypothesis can result in the creation of theories. When supported by substantive evidence, hypothesis can serve as the foundation for larger theoretical frameworks that explain complex phenomena.
• Beyond scientific research, hypothesis play a role in the solution of problems in a variety of domains. They enable professionals to make educated assumptions about the causes of problems and to devise solutions.

Research Hypotheses: Did you know that a hypothesis refers to an educated guess or prediction about the outcome of a research study?

It’s like a roadmap guiding researchers towards their destination of knowledge. Just like a compass points north, a well-crafted hypothesis points the way to valuable discoveries in the world of science and inquiry.

Choose the best answer. 

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Further Reading

• RNA-DNA World Hypothesis
• BYJU’S. (2023). Hypothesis. Retrieved 01 Septermber 2023, from https://byjus.com/physics/hypothesis/#sources-of-hypothesis
• Collegedunia. (2023). Hypothesis. Retrieved 1 September 2023, from https://collegedunia.com/exams/hypothesis-science-articleid-7026#d
• Hussain, D. J. (2022). Hypothesis. Retrieved 01 September 2023, from https://mmhapu.ac.in/doc/eContent/Management/JamesHusain/Research%20Hypothesis%20-Meaning,%20Nature%20&%20Importance-Characteristics%20of%20Good%20%20Hypothesis%20Sem2.pdf
• Media, D. (2023). Hypothesis in the Scientific Method. Retrieved 01 September 2023, from https://www.verywellmind.com/what-is-a-hypothesis-2795239#toc-hypotheses-examples
• Rashid, M. H. A. (Apr 20, 2022). Research Methodology. Retrieved 01 September 2023, from https://limbd.org/hypothesis-definitions-functions-characteristics-types-errors-the-process-of-testing-a-hypothesis-hypotheses-in-qualitative-research/#:~:text=Functions%20of%20a%20Hypothesis%3A&text=Specifically%2C%20a%20hypothesis%20serves%20the,providing%20focus%20to%20the%20study.

©BiologyOnline.com. Content provided and moderated by Biology Online Editors.

Last updated on September 8th, 2023

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Meaning of hypothesis in English

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• abstraction
• accepted wisdom
• afterthought
• anthropocentrism
• determinist
• non-dogmatic
• non-empirical
• social Darwinism
• supersensible
• the domino theory

hypothesis | American Dictionary

Hypothesis | business english, examples of hypothesis, translations of hypothesis.

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enterprising

good at thinking of and doing new and difficult things, especially things that will make money

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Definition of hypothesis noun from the Oxford Advanced Learner's Dictionary

• to formulate/confirm a hypothesis
• a hypothesis about the function of dreams
• There is little evidence to support these hypotheses.
• formulate/​advance a theory/​hypothesis
• build/​construct/​create/​develop a simple/​theoretical/​mathematical model
• develop/​establish/​provide/​use a theoretical/​conceptual framework
• advance/​argue/​develop the thesis that…
• explore an idea/​a concept/​a hypothesis
• make a prediction/​an inference
• base a prediction/​your calculations on something
• investigate/​evaluate/​accept/​challenge/​reject a theory/​hypothesis/​model
• design an experiment/​a questionnaire/​a study/​a test
• do research/​an experiment/​an analysis
• make observations/​measurements/​calculations
• carry out/​conduct/​perform an experiment/​a test/​a longitudinal study/​observations/​clinical trials
• run an experiment/​a simulation/​clinical trials
• repeat an experiment/​a test/​an analysis
• replicate a study/​the results/​the findings
• observe/​study/​examine/​investigate/​assess a pattern/​a process/​a behaviour
• fund/​support the research/​project/​study
• seek/​provide/​get/​secure funding for research
• collect/​gather/​extract data/​information
• yield data/​evidence/​similar findings/​the same results
• analyse/​examine the data/​soil samples/​a specimen
• consider/​compare/​interpret the results/​findings
• fit the data/​model
• confirm/​support/​verify a prediction/​a hypothesis/​the results/​the findings
• prove a conjecture/​hypothesis/​theorem
• draw/​make/​reach the same conclusions
• read/​review the records/​literature
• describe/​report an experiment/​a study
• present/​publish/​summarize the results/​findings
• present/​publish/​read/​review/​cite a paper in a scientific journal
• Her hypothesis concerns the role of electromagnetic radiation.
• Her study is based on the hypothesis that language simplification is possible.
• It is possible to make a hypothesis on the basis of this graph.
• None of the hypotheses can be rejected at this stage.
• Scientists have proposed a bold hypothesis.
• She used this data to test her hypothesis
• The hypothesis predicts that children will perform better on task A than on task B.
• The results confirmed his hypothesis on the use of modal verbs.
• These observations appear to support our working hypothesis.
• a speculative hypothesis concerning the nature of matter
• an interesting hypothesis about the development of language
• Advances in genetics seem to confirm these hypotheses.
• His hypothesis about what dreams mean provoked a lot of debate.
• Research supports the hypothesis that language skills are centred in the left side of the brain.
• The survey will be used to test the hypothesis that people who work outside the home are fitter and happier.
• This economic model is really a working hypothesis.
• speculative
• concern something
• be based on something
• predict something
• on a/​the hypothesis
• hypothesis about
• hypothesis concerning

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hypothesist noun

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What does the noun hypothesist mean?

There is one meaning in OED's entry for the noun hypothesist . See ‘Meaning & use’ for definition, usage, and quotation evidence.

Entry status

OED is undergoing a continuous programme of revision to modernize and improve definitions. This entry has not yet been fully revised.

How common is the noun hypothesist ?

Where does the noun hypothesist come from?

Earliest known use

The earliest known use of the noun hypothesist is in the late 1700s.

OED's only evidence for hypothesist is from 1788, in the writing of Thomas Jefferson, revolutionary politician and president of the United States of America.

hypothesist is formed within English, by derivation.

Etymons: hypothesis n. , ‑t suffix 3

Nearby entries

• hypothecary, adj. 1656–
• hypothecate, v. 1693–
• hypothecation, n. 1681–
• hypothecative, adj. 1856–
• hypothecator, n. 1828–
• hypothecium, n. 1866–
• hypothenar, adj. 1706–
• hypothermia, n. 1886–
• hypothermic, adj. 1898–
• hypothesis, n. 1596–
• hypothesist, n. 1788–
• hypothesize, v. 1738–
• hypothesizer, n. 1833–
• hypothetic, adj. & n. a1680–
• hypothetical, adj. & n. 1588–
• hypothetically, adv. 1628–
• hypothetico-deductive, adj. 1912–
• hypothetico-deductively, adv. 1953–
• hypothetico-disjunctive, adj. & n. a1856–
• hypothetist, n. 1852–
• hypothetize, v. 1895–

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Meaning & use

Entry history for hypothesist, n..

Originally published as part of the entry for hypothesis, n.

hypothesis, n. was first published in 1899; not yet revised.

Revision of the OED is a long-term project. Entries in oed.com which have not been revised may include:

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• new senses, phrases, and quotations which have been added in subsequent print and online updates.

Earlier versions of this entry were published in:

OED First Edition (1899)

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OED Second Edition (1989)

• View hypothesis in OED Second Edition

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Citation details

Factsheet for hypothesist, n., browse entry.

Look up a word, learn it forever.

/haɪˈpɑθəsəs/, /haɪˈpɒθɪsɪs/.

Other forms: hypotheses

In science, a hypothesis is an idea or explanation that you then test through study and experimentation. Outside science, a theory or guess can also be called a hypothesis .

A hypothesis is something more than a wild guess but less than a well-established theory. In science, a hypothesis needs to go through a lot of testing before it gets labeled a theory. In the non-scientific world, the word is used a lot more loosely. A detective might have a hypothesis about a crime, and a mother might have a hypothesis about who spilled juice on the rug. Anyone who uses the word hypothesis is making a guess.

• noun a tentative insight into the natural world; a concept that is not yet verified but that if true would explain certain facts or phenomena “a scientific hypothesis that survives experimental testing becomes a scientific theory” synonyms: possibility , theory see more see less types: show 17 types... hide 17 types... hypothetical a hypothetical possibility, circumstance, statement, proposal, situation, etc. gemmule the physically discrete element that Darwin proposed as responsible for heredity framework , model , theoretical account a hypothetical description of a complex entity or process conjecture , speculation a hypothesis that has been formed by speculating or conjecturing (usually with little hard evidence) assumption , supposal , supposition a hypothesis that is taken for granted historicism a theory that social and cultural events are determined by history computer simulation , simulation (computer science) the technique of representing the real world by a computer program conclusion an intuitive assumption base , basis , cornerstone , foundation , fundament , groundwork the fundamental assumptions from which something is begun or developed or calculated or explained mean sun a theoretical sun that moves along the celestial equator at a constant speed and completes its annual course in the same amount of time the real sun takes at variable speeds Copernican system (astronomy) Copernicus' astronomical model in which the Earth rotates around the sun Ptolemaic system (astronomy) Ptolemy's model of the universe with the Earth at the center M-theory (particle physics) a theory that involves an eleven-dimensional universe in which the weak and strong forces and gravity are unified and to which all the string theories belong string theory (particle physics) a theory that postulates that subatomic particles are one-dimensional strings given , precondition , presumption an assumption that is taken for granted basic assumption , constatation , self-evident truth an assumption that is basic to an argument stochastic process a statistical process involving a number of random variables depending on a variable parameter (which is usually time) type of: concept , conception , construct an abstract or general idea inferred or derived from specific instances
• noun a proposal intended to explain certain facts or observations see more see less type of: proposal something proposed (such as a plan or assumption)
• noun a message expressing an opinion based on incomplete evidence synonyms: conjecture , guess , speculation , supposition , surmisal , surmise see more see less types: divination successful conjecture by unusual insight or good luck type of: opinion , view a message expressing a belief about something; the expression of a belief that is held with confidence but not substantiated by positive knowledge or proof

Vocabulary lists containing hypothesis

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What is Hypothesis? Definition, Meaning, Characteristics, Sources

• Post last modified: 10 January 2022
• Reading time: 18 mins read
• Post category: Research Methodology

• What is Hypothesis?

Hypothesis is a prediction of the outcome of a study. Hypotheses are drawn from theories and research questions or from direct observations. In fact, a research problem can be formulated as a hypothesis. To test the hypothesis we need to formulate it in terms that can actually be analysed with statistical tools.

As an example, if we want to explore whether using a specific teaching method at school will result in better school marks (research question), the hypothesis could be that the mean school marks of students being taught with that specific teaching method will be higher than of those being taught using other methods.

In this example, we stated a hypothesis about the expected differences between groups. Other hypotheses may refer to correlations between variables.

Table of Content

• 1 What is Hypothesis?
• 2 Hypothesis Definition
• 3 Meaning of Hypothesis
• 4.1 Conceptual Clarity
• 4.2 Need of empirical referents
• 4.3 Hypothesis should be specific
• 4.4 Hypothesis should be within the ambit of the available research techniques
• 4.5 Hypothesis should be consistent with the theory
• 4.6 Hypothesis should be concerned with observable facts and empirical events
• 4.7 Hypothesis should be simple
• 5.1 Observation
• 5.2 Analogies
• 5.4 State of Knowledge
• 5.5 Culture
• 5.6 Continuity of Research
• 6.1 Null Hypothesis
• 6.2 Alternative Hypothesis

Thus, to formulate a hypothesis, we need to refer to the descriptive statistics (such as the mean final marks), and specify a set of conditions about these statistics (such as a difference between the means, or in a different example, a positive or negative correlation). The hypothesis we formulate applies to the population of interest.

The null hypothesis makes a statement that no difference exists (see Pyrczak, 1995, pp. 75-84).

Hypothesis Definition

A hypothesis is ‘a guess or supposition as to the existence of some fact or law which will serve to explain a connection of facts already known to exist.’ – J. E. Creighton & H. R. Smart

Hypothesis is ‘a proposition not known to be definitely true or false, examined for the sake of determining the consequences which would follow from its truth.’ – Max Black

Hypothesis is ‘a proposition which can be put to a test to determine validity and is useful for further research.’ – W. J. Goode and P. K. Hatt

A hypothesis is a proposition, condition or principle which is assumed, perhaps without belief, in order to draw out its logical consequences and by this method to test its accord with facts which are known or may be determined. – Webster’s New International Dictionary of the English Language (1956)

Meaning of Hypothesis

From the above mentioned definitions of hypothesis, its meaning can be explained in the following ways.

• At the primary level, a hypothesis is the possible and probable explanation of the sequence of happenings or data.
• Sometimes, hypothesis may emerge from an imagination, common sense or a sudden event.
• Hypothesis can be a probable answer to the research problem undertaken for study. 4. Hypothesis may not always be true. It can get disproven. In other words, hypothesis need not always be a true proposition.
• Hypothesis, in a sense, is an attempt to present the interrelations that exist in the available data or information.
• Hypothesis is not an individual opinion or community thought. Instead, it is a philosophical means which is to be used for research purpose. Hypothesis is not to be considered as the ultimate objective; rather it is to be taken as the means of explaining scientifically the prevailing situation.

The concept of hypothesis can further be explained with the help of some examples. Lord Keynes, in his theory of national income determination, made a hypothesis about the consumption function. He stated that the consumption expenditure of an individual or an economy as a whole is dependent on the level of income and changes in a certain proportion.

Later, this proposition was proved in the statistical research carried out by Prof. Simon Kuznets. Matthus, while studying the population, formulated a hypothesis that population increases faster than the supply of food grains. Population studies of several countries revealed that this hypothesis is true.

Validation of the Malthus’ hypothesis turned it into a theory and when it was tested in many other countries it became the famous Malthus’ Law of Population. It thus emerges that when a hypothesis is tested and proven, it becomes a theory. The theory, when found true in different times and at different places, becomes the law. Having understood the concept of hypothesis, few hypotheses can be formulated in the areas of commerce and economics.

• Population growth moderates with the rise in per capita income.
• Sales growth is positively linked with the availability of credit.
• Commerce education increases the employability of the graduate students.
• High rates of direct taxes prompt people to evade taxes.
• Good working conditions improve the productivity of employees.
• Advertising is the most effecting way of promoting sales than any other scheme.
• Higher Debt-Equity Ratio increases the probability of insolvency.
• Economic reforms in India have made the public sector banks more efficient and competent.
• Foreign direct investment in India has moved in those sectors which offer higher rate of profit.
• There is no significant association between credit rating and investment of fund.

Characteristics of Hypothesis

Not all the hypotheses are good and useful from the point of view of research. It is only a few hypotheses satisfying certain criteria that are good, useful and directive in the research work undertaken. The characteristics of such a useful hypothesis can be listed as below:

Conceptual Clarity

Need of empirical referents, hypothesis should be specific, hypothesis should be within the ambit of the available research techniques, hypothesis should be consistent with the theory, hypothesis should be concerned with observable facts and empirical events, hypothesis should be simple.

The concepts used while framing hypothesis should be crystal clear and unambiguous. Such concepts must be clearly defined so that they become lucid and acceptable to everyone. How are the newly developed concepts interrelated and how are they linked with the old one is to be very clear so that the hypothesis framed on their basis also carries the same clarity.

A hypothesis embodying unclear and ambiguous concepts can to a great extent undermine the successful completion of the research work.

A hypothesis can be useful in the research work undertaken only when it has links with some empirical referents. Hypothesis based on moral values and ideals are useless as they cannot be tested. Similarly, hypothesis containing opinions as good and bad or expectation with respect to something are not testable and therefore useless.

For example, ‘current account deficit can be lowered if people change their attitude towards gold’ is a hypothesis encompassing expectation. In case of such a hypothesis, the attitude towards gold is something which cannot clearly be described and therefore a hypothesis which embodies such an unclean thing cannot be tested and proved or disproved. In short, the hypothesis should be linked with some testable referents.

For the successful conduction of research, it is necessary that the hypothesis is specific and presented in a precise manner. Hypothesis which is general, too ambitious and grandiose in scope is not to be made as such hypothesis cannot be easily put to test. A hypothesis is to be based on such concepts which are precise and empirical in nature. A hypothesis should give a clear idea about the indicators which are to be used.

For example, a hypothesis that economic power is increasingly getting concentrated in a few hands in India should enable us to define the concept of economic power. It should be explicated in terms of measurable indicator like income, wealth, etc. Such specificity in the formulation of a hypothesis ensures that the research is practicable and significant.

While framing the hypothesis, the researcher should be aware of the available research techniques and should see that the hypothesis framed is testable on the basis of them. In other words, a hypothesis should be researchable and for this it is important that a due thought has been given to the methods and techniques which can be used to measure the concepts and variables embodied in the hypothesis.

It does not however mean that hypotheses which are not testable with the available techniques of research are not to be made. If the problem is too significant and therefore the hypothesis framed becomes too ambitious and complex, it’s testing becomes possible with the development of new research techniques or the hypothesis itself leads to the development of new research techniques.

A hypothesis must be related to the existing theory or should have a theoretical orientation. The growth of knowledge takes place in the sequence of facts, hypothesis, theory and law or principles. It means the hypothesis should have a correspondence with the existing facts and theory.

If the hypothesis is related to some theory, the research work will enable us to support, modify or refute the existing theory. Theoretical orientation of the hypothesis ensures that it becomes scientifically useful. According to Prof. Goode and Prof. Hatt, research work can contribute to the existing knowledge only when the hypothesis is related with some theory.

This enables us to explain the observed facts and situations and also verify the framed hypothesis. In the words of Prof. Cohen and Prof. Nagel, “hypothesis must be formulated in such a manner that deduction can be made from it and that consequently a decision can be reached as to whether it does or does not explain the facts considered.”

If the research work based on a hypothesis is to be successful, it is necessary that the later is as simple and easy as possible. An ambition of finding out something new may lead the researcher to frame an unrealistic and unclear hypothesis. Such a temptation is to be avoided. Framing a simple, easy and testable hypothesis requires that the researcher is well acquainted with the related concepts.

Sources of Hypothesis

Hypotheses can be derived from various sources. Some of the sources is given below:

Observation

State of knowledge, continuity of research.

Hypotheses can be derived from observation from the observation of price behavior in a market. For example the relationship between the price and demand for an article is hypothesized.

Analogies are another source of useful hypotheses. Julian Huxley has pointed out that casual observations in nature or in the framework of another science may be a fertile source of hypotheses. For example, the hypotheses that similar human types or activities may be found in similar geophysical regions come from plant ecology.

This is one of the main sources of hypotheses. It gives direction to research by stating what is known logical deduction from theory lead to new hypotheses. For example, profit / wealth maximization is considered as the goal of private enterprises. From this assumption various hypotheses are derived’.

An important source of hypotheses is the state of knowledge in any particular science where formal theories exist hypotheses can be deduced. If the hypotheses are rejected theories are scarce hypotheses are generated from conception frameworks.

Another source of hypotheses is the culture on which the researcher was nurtured. Western culture has induced the emergence of sociology as an academic discipline over the past decade, a large part of the hypotheses on American society examined by researchers were connected with violence. This interest is related to the considerable increase in the level of violence in America.

The continuity of research in a field itself constitutes an important source of hypotheses. The rejection of some hypotheses leads to the formulation of new ones capable of explaining dependent variables in subsequent research on the same subject.

Null and Alternative Hypothesis

Null hypothesis.

The hypothesis that are proposed with the intent of receiving a rejection for them are called Null Hypothesis . This requires that we hypothesize the opposite of what is desired to be proved. For example, if we want to show that sales and advertisement expenditure are related, we formulate the null hypothesis that they are not related.

Similarly, if we want to conclude that the new sales training programme is effective, we formulate the null hypothesis that the new training programme is not effective, and if we want to prove that the average wages of skilled workers in town 1 is greater than that of town 2, we formulate the null hypotheses that there is no difference in the average wages of the skilled workers in both the towns.

Since we hypothesize that sales and advertisement are not related, new training programme is not effective and the average wages of skilled workers in both the towns are equal, we call such hypotheses null hypotheses and denote them as H 0 .

Alternative Hypothesis

Rejection of null hypotheses leads to the acceptance of alternative hypothesis . The rejection of null hypothesis indicates that the relationship between variables (e.g., sales and advertisement expenditure) or the difference between means (e.g., wages of skilled workers in town 1 and town 2) or the difference between proportions have statistical significance and the acceptance of the null hypotheses indicates that these differences are due to chance.

As already mentioned, the alternative hypotheses specify that values/relation which the researcher believes hold true. The alternative hypotheses can cover a whole range of values rather than a single point. The alternative hypotheses are denoted by H 1 .

Business Ethics

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• What is Ethics?
• What is Business Ethics?
• Values, Norms, Beliefs and Standards in Business Ethics
• Indian Ethos in Management
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• What is Risk Register?
• Risk Management Committee

Corporate social responsibility (CSR)

• Theories of CSR
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• Importance of CSR in India
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• Developing a CSR Strategy
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• CSR Marketplace
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• CSR with Communities and in Supply Chain
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• What is Corporate Ethics?

Lean Six Sigma

• What is Six Sigma?
• What is Lean Six Sigma?
• Value and Waste in Lean Six Sigma
• Six Sigma Team
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• What is Binomial, Poisson, Normal Distribution?
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• What is Process Audits?
• Six Sigma Implementation at Ford
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• What is Research?
• Sampling Method
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Data Collection in Research

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Levels of Measurement

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Operations Research

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• Transportation Problem Initial Basic Feasible Solution
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• Project Network Analysis with Critical Path Method
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• Simulation in Operation Research
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Operation Management

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• Supply Chain Process Restructuring
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• Re-engineering Improvement in SCM
• What is Supply Chain Drivers?
• Supply Chain Operations Reference (SCOR) Model
• Customer Service and Cost Trade Off
• Internal and External Performance Measures
• Linking Supply Chain and Business Performance
• Netflix’s Niche Focused Strategy
• Disney and Pixar Merger
• Process Planning at Mcdonald’s

Service Operations Management

• What is Service?
• What is Service Operations Management?
• What is Service Design?
• Service Design Process
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• What is Service Quality?
• Gap Model of Service Quality
• Juran Trilogy
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Procurement Management

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• Procurement Negotiation
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hypothecate (v.)

1680s, "pledge (something) without giving up control of it; pawn; mortgage," from hypothecat- , past-participle stem of Medieval Latin hypothecare , from Late Latin hypotheca "a pledge," from Greek hypothēkē "a deposit, pledge, mortgage," from hypo- "beneath, under" (see hypo- ) + tithenai "to put, to place," from reduplicated form of PIE root *dhe- "to set, put." Related: Hypothecated ; hypothecating ; hypothecation ; hypothecary .

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*dhē- , Proto-Indo-European root meaning "to set, put."

It forms all or part of: abdomen ; abscond ; affair ; affect (v.1) "make a mental impression on;" affect (v.2) "make a pretense of;" affection ; amplify ; anathema ; antithesis ; apothecary ; artifact ; artifice ; beatific ; benefice ; beneficence ; beneficial ; benefit ; bibliothec ; bodega ; boutique ; certify ; chafe ; chauffeur ; comfit ; condiment ; confection ; confetti ; counterfeit ; deed ; deem ; deface ; defeasance ; defeat ; defect ; deficient ; difficulty ; dignify ; discomfit ; do (v.); doom ; -dom ; duma ; edifice ; edify ; efface ; effect ; efficacious ; efficient ; epithet ; facade ; face ; facet ; facial ; -facient ; facile ; facilitate ; facsimile ; fact ; faction (n.1) "political party;" -faction ; factitious ; factitive ; factor ; factory ; factotum ; faculty ; fashion ; feasible ; feat ; feature ; feckless ; fetish ; -fic ; fordo ; forfeit ; -fy ; gratify ; hacienda ; hypothecate ; hypothesis ; incondite ; indeed ; infect ; justify ; malefactor ; malfeasance ; manufacture ; metathesis ; misfeasance ; modify ; mollify ; multifarious ; notify ; nullify ; office ; officinal ; omnifarious ; orifice ; parenthesis ; perfect ; petrify ; pluperfect ; pontifex ; prefect ; prima facie ; proficient ; profit ; prosthesis ; prothesis ; purdah ; putrefy ; qualify ; rarefy ; recondite ; rectify ; refectory ; sacrifice ; salmagundi ; samadhi ; satisfy ; sconce ; suffice ; sufficient ; surface ; surfeit ; synthesis ; tay ; ticking (n.); theco- ; thematic ; theme ; thesis ; verify .

It is the hypothetical source of/evidence for its existence is provided by: Sanskrit dadhati "puts, places;" Avestan dadaiti "he puts;" Old Persian ada "he made;" Hittite dai- "to place;" Greek tithenai "to put, set, place;" Latin facere "to make, do; perform; bring about;" Lithuanian dėti "to put;" Polish dziać się "to be happening;" Russian delat' "to do;" Old High German tuon , German tun , Old English don "to do."

word-forming element meaning "under, beneath; less, less than" (in chemistry, indicating a lesser oxidation), from Greek hypo (prep. and adverb) "under, beneath; up from under; toward and under (i.e. into)," from PIE root *upo "under."

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Origin of Flowers: Evolutionists Don’t Even Know What They Don’t Know

A damaging preprint claims that data on the origin of flowers is heavily biased

Add this to the “Darwin was wrong” department. Include all his followers, too.

Suppose a pollster tried to gauge the mood of the country by only interviewing students at Columbia University. Would the results be reliable? That’s a bit like the complaint lodged against evolutionary biologists by evolutionists about bias in the data used to infer the origin of flowering plants.

Meyer, Galloway and Eckert, writing in the biology preprint service bioRxiv on June 19 , begin by dredging up Darwin’s well-known frustration trying to explain the explosive appearance and rapid diversification of flowering plants (angiosperms) in the fossil record:

An “abominable mystery”: angiosperm sexual systems have been a source of both interest and frustration for the botanical community since Darwin. The evolutionary stability , overall frequency, and distribution of self-fertilization and mixed-mating systems have been addressed in a variety of studies. However, there has been no recent study which directly addresses our knowledge of mating systems across families, the adequacy of existing data, or the potential for biases.

Notice that the frustration has been experienced not just by Charley, but by all his disciples in the 167 years since The Origin . Meyer et al. decided to investigate.

Here, we present an updated dataset of mating systems across flowering plants covering 6,781 species and 212 families. We find that the vast majority of our data on mating systems comes from a small number of disproportionally-sampled families, and that families with significant proportions of dioecious or monoecious species are much more likely to be undersampled . This suggests that systematic study bias may mean we know less about this vital facet of plant life than we think.

Systematic bias. Undersampling. Like the pollster at Columbia, this is not good. Plant evolutionists have tended to study the “interesting” cases

But perhaps better sampling would help Charley get over his stomach pains by solving the abominable and abdominal mystery. Do the authors think that is a possibility? Well, if so, not yet. The answer lies in the nebulous mists of futureware .

By assembling existing knowledge of selfing in an updated, harmonized, and publicly available dataset, we hope to promote further research in the rich field of plant reproductive systems. We especially hope to encourage studies which address the underlying distribution of selfing in angiosperms, and selfing-focused papers broadly to consider the adequacy of existing data. We also hope to promote additional investigation into as-of-yet understudied groups , such as understudied families with dioecious and monoecious species, or families which have been shown to be especially under-represented compared to their species diversity.

The authors note that inbreeding depression could lead to extinction (see bottom of this article for discussion).

The variety among angiosperms is astonishing. They abruptly appear in the fossil record.

Did Darwin Bring Understanding?

In their ending discussion, the authors admit with Tontological phraseology, “Our results suggest that we understand less about the underlying frequency of selfing across angiosperms than was previously thought. ” Who previously thought that? “We” evolutionists.

Overcoming bias will require not only better sampling but a wider perspective. “As illustrated by our work, it will also be vital that we utilize a more holistic view of plant reproduction,” they say. From there, their preprint descends into Darwinese and climate change.

In an era of unprecedented anthropogenic disturbance , it thus seems plausible that an individual plant’s reproductive strategy could become a stronger predictor of its fitness than it has been in the past.

See “Fitness for Dummies,” 19 June 2014 . Notice that there are no scientific laws of plausibility. Plausibility is in the eye of the beholder. Having admitted to bias and lack of understanding (“we understand less”) in their field of evolutionary botany, should their evidence-free plausibility measure (“seems plausible”) be given any more credence than the opinion of a biased pollster?

Status of Darwin’s Abominable Mystery

Now to the crux of the issue: did these authors solve Darwin’s abominable mystery? Or did they at least contribute with more data to the possibility of solving it? No. They only said that all previous studies were based on data that were systematically biased. In their last sentence, they admit that finding so much bias in the samples “illustrates the importance of understanding the prevalence of outcrossing, selfing and mixed-mating across angiosperms.” Earlier, they emphasized the risks of doing science with poor sampling:

Similarly, if our understanding of the true underlying distribution of selfing is biased , then we run the risk of making incorrect and overly simplifying assumptions when modeling mating system evolution with use of PCMs [ phylogenetic comparative methods , an evolutionary approach to classifying plants]. Incorrect or biased assumptions, moreover, may more generally lead us to incorrect conclusions , even when estimating quantities as simple as the frequency of selfing and mixed mating across angiosperms.

Back to the drawing board.

We’ve given the Darwinians 165 years to figure out their mystery. How much longer do they deserve? Time’s up.

How much “understanding” did these evolutionary biologists deliver? Do you like it? Is it satisfying? Consider a different source of understanding.

You, through Your commandments, make me wiser than my enemies; For they are ever with me. I have more understanding than all my teachers, For Your testimonies are my meditation. I understand more than the ancients, Because I keep Your precepts. Psalm 119:98-100

Addendum: Selfing and Mutational Meltdown

Because inbreeding could be an “evolutionary dead end,” it would have been advantageous, therefore, for plants to “evolve” more cases of outcrossing instead of self-pollinization, or “selfing”. The authors found systematic biases in the data: “our collective knowledge about the underlying distribution of selfing, if based on meta-analyses using these studies, will likely be biased.”

If selfing is an evolutionary dead end, why does it appear so often?

Considerable theoretical work has evaluated the evolutionary costs and benefits of selfing (Darwin 1876 ; Fisher 1941; Nagylacki 1976; Lloyd 1977, 1979, 1980; Cheptou 2019). Most straightforwardly, self-fertilization holds a transmission advantage of gene copies over two-parent reproduction (Fisher 1941). Based on this alone, without an evolutionary cost to selfing , it would become commonplace. The obvious evolutionary cost to selfing is the increased expression of recessive deleterious phenotypes leading to inbreeding depression. Thus, to explain the variation we observe in plant reproductive systems, we must explain both the continued existence of selfing plants in the face of inbreeding depression and the persistence of outcrossing in spite of the two-fold transmission advantage of selfing. The fitness cost incurred by inbreeding depression (Charlesworth and Charlesworth 1987) may explain why selfing does not outcompete outcrossing based on transmission advantage alone (Lloyd 1979). Under circumstances where the cost of inbreeding depression does not outweigh the transmission advantage of selfing, however, selfing can still persist (Lloyd 1979). Another commonly cited advantage of selfing is reproductive assurance in the absence of a mate , or pollen limitation ( Darwin 1876 ; Kalisz 2004; reviewed by Busch and Delph 2012). Selfing has thus also been proposed as a mechanism to aid colonization of new habitats, with self-compatible organisms more likely to be successful colonizers than self-incompatible species (Baker 1955). This is also sometimes referred to as “Baker’s Law.”

Other parts of the discussion waffle between “it could be this” or “it could be that.” But even now, the authors admit that “we remain extremely uncertain about what percentage of angiosperm species are capable of selfing.”

Regardless of the direction of this interaction, the inevitable result is that our understanding of the evolution , ecological characteristics, and frequency of selfing arises disproportionately from a limited number of families that may not be representative of angiosperms overall.

Here’s another outcome of persistent selfing in plants: mutational meltdown. Why hasn’t it happened?

From this body of literature, two prominent – but not mutually exclusive – hypotheses emerged about the expected frequency of selfing across angiosperms. Stebbins (1957) proposed that selfing is an evolutionary “dead end,” with selfing species more prone to extinction. He suggested that the limitations placed on genetic diversity by selfing would constrain adaptation to new environments. This hypothesis suggests, even if the deleterious alleles associated with inbreeding depression could be purged, that over time the loss of genetic diversity would doom selfing species to extinction. However, if transitions to selfing were sufficiently frequent , at any given point in evolutionary time , we could still potentially observe extant selfing species (Stebbins 1957). Schemske and Lande (1985) proposed that the distribution of selfing should be bimodal , with most species either primarily selfing or primarily outcrossing. Outcrossing would represent a stable strategy by avoiding inbreeding depression and promoting diversity through biparental sexual reproduction. Similarly, highly selfing species would be able to avoid inbreeding depression by purging deleterious alleles and would thus persist due to their transmission advantage and reproductive assurance. Species with mixed mating, however, should be less common, as purging of deleterious alleles would be more difficult under intermediate levels of selfing, yet the risks of inbreeding depression and loss of genetic diversity remain.

Neither hypothesis rises above the level of anecdote. The authors point to a subsequent “wealth of empirical papers addressing selfing in various plant systems” since Stebbins, Schemske and Lande. “However, this larger dataset has the potential to continue promoting the existing biases” identified by these authors and others.

Here’s a solution: “evolutionary time” is a myth. Selfing plants have not been around long enough to suffer extensive inbreeding depression and extinction. They were created thousands of years ago, not hundreds of millions of years ago. Once again, belief in Deep Time is a problem, not a solution.

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• Published: 26 June 2024

Synaptic architecture of leg and wing premotor control networks in Drosophila

• Ellen Lesser 1   na1 ,
• Anthony W. Azevedo   ORCID: orcid.org/0000-0001-8318-9678 1   na1 ,
• Jasper S. Phelps 2   nAff11 ,
• Leila Elabbady 1 ,
• Andrew Cook 1 ,
• Durafshan Sakeena Syed 3 ,
• Brandon Mark 1 ,
• Sumiya Kuroda 2 ,
• Anne Sustar 1 ,
• Anthony Moussa 1 ,
• Chris J. Dallmann 1 ,
• Sweta Agrawal 1 ,
• Su-Yee J. Lee 1 ,
• Brandon Pratt 1 ,
• Kyobi Skutt-Kakaria 4 ,
• Stephan Gerhard 2 , 5 ,
• Nico Kemnitz 6 ,
• Kisuk Lee 6 , 7 ,
• Akhilesh Halageri 6 ,
• Manuel Castro 6 ,
• Dodam Ih 6 ,
• Jay Gager   ORCID: orcid.org/0000-0002-8001-2604 6 ,
• Marwan Tammam 6 ,
• Sven Dorkenwald 7 , 8 ,
• Forrest Collman   ORCID: orcid.org/0000-0002-0280-7022 9 ,
• Casey Schneider-Mizell   ORCID: orcid.org/0000-0001-9477-3853 9 ,
• Derrick Brittain 9 ,
• Chris S. Jordan 7 ,
• Thomas Macrina   ORCID: orcid.org/0000-0002-0622-9338 6 ,
• Michael Dickinson   ORCID: orcid.org/0000-0002-8587-9936 4 ,
• Wei-Chung Allen Lee   ORCID: orcid.org/0000-0002-4618-295X 2 , 10 &
• John C. Tuthill   ORCID: orcid.org/0000-0002-5689-5806 1  

Nature ( 2024 ) Cite this article

Metrics details

• Neural circuits
• Spinal cord

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles 1 . MN activity is coordinated by complex premotor networks that facilitate the contribution of individual muscles to many different behaviours 2 , 3 , 4 , 5 , 6 . Here we use connectomics 7 to analyse the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. By contrast, wing premotor networks lack proportional synaptic connectivity, which may enable more flexible recruitment of wing steering muscles. Through comparison of the architecture of distinct motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

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Data availability

The data presented in the paper were analysed from CAVE materialization version 840 (v.840). Annotated connectivity matrices (Fig. 2 ) are available as Python Pandas data frames ( https://pandas.pydata.org/ ) at GitHub ( https://github.com/tuthill-lab/Lesser_Azevedo_2023 ). Links to public preMN and MN segmentations are available throughout the text, as well as in Supplementary Tables 1 – 3 .

Code availability

Scripts to recreate the analyses and figures in the paper, as well as scripts to recreate the connectivity matrices, are available at GitHub ( https://github.com/tuthill-lab/Lesser_Azevedo_2023 ) for users authorized to interact with the CAVEclient. All analysis was performed in Python 3.9 using custom code, making extensive use of CAVEclient ( https://github.com/seung-lab/CAVEclient ) 65 and CloudVolume to interact with data infrastructure, and the libraries Matplotlib, Numpy, Pandas, Scikit-learn, Scipy, stats-models and VTK for general computation, machine learning and data visualization. Additional code is available at https://github.com/htem/FANC_auto_recon , providing additional tutorials, documentation for interaction with FANC and instructions for joining the FANC community.

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Acknowledgements

This work was supported by a Searle Scholar Award, a Klingenstein-Simons Fellowship, a Pew Biomedical Scholar Award, a McKnight Scholar Award, a Sloan Research Fellowship, the New York Stem Cell Foundation and a UW Innovation Award to J.C.T.; a Genise Goldenson Award to W.-C.A.L.; NIH no. U19NS104655 to J.C.T. and M.D.; 1RF1NS128785-01 to J.C.T.; and NIH no. R01MH117808 to J.C.T. and W.-C.A.L. J.C.T. is a New York Stem Cell Foundation – Robertson Investigator. We thank J. Truman, D. Shepherd and E. Marin for assistance with hemilineage identification. We thank H. Lacin, L. Marin, G. Jefferis amd G. Card for helpful discussions, and for their laboratory’s contributions to proofreading in the FANC dataset, in particular K. Eichler, P. Brooks, T. Stürner, M. Costa and G. Jefferis for sharing comprehensive proofreading and annotation of neck connective neurons including descending and ascending neurons in the FANC dataset (supported by Wellcome award 221300/Z/20/Z). We thank members of the Tuthill and Dickinson Laboratories, S. Ahmed, B. Brunton and J. Truman for comments on the manuscript.

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Jasper S. Phelps

Present address: Neuroengineering Laboratory, Brain Mind Institute and Institute of Bioengineering, EPFL, Lausanne, Switzerland

These authors contributed equally: Ellen Lesser, Anthony W. Azevedo

Authors and Affiliations

Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA

Ellen Lesser, Anthony W. Azevedo, Leila Elabbady, Andrew Cook, Brandon Mark, Anne Sustar, Anthony Moussa, Chris J. Dallmann, Sweta Agrawal, Su-Yee J. Lee, Brandon Pratt & John C. Tuthill

Department of Neurobiology, Harvard Medical School, Boston, MA, USA

Jasper S. Phelps, Sumiya Kuroda, Stephan Gerhard & Wei-Chung Allen Lee

University of California, Santa Barbara, CA, USA

Durafshan Sakeena Syed

California Institute of Technology, Pasadena, CA, USA

Kyobi Skutt-Kakaria & Michael Dickinson

UniDesign Solutions LLC, Zurich, Switzerland

Stephan Gerhard

Zetta AI, LLC, Sherrill, NY, USA

Ran Lu, Nico Kemnitz, Kisuk Lee, Akhilesh Halageri, Manuel Castro, Dodam Ih, Jay Gager, Marwan Tammam & Thomas Macrina

Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA

Kisuk Lee, Sven Dorkenwald & Chris S. Jordan

Computer Science Department, Princeton University, Princeton, NJ, USA

Sven Dorkenwald

Allen Institute for Brain Science, Seattle, WA, USA

Forrest Collman, Casey Schneider-Mizell & Derrick Brittain

F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

Wei-Chung Allen Lee

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Contributions

E.L., A.W.A., W.-C.A.L. and J.C.T. conceived the project. W.-C.A.L. and J.C.T. acquired funding. R.L., N.K., K.L., A.H., M.C., D.I., J.G., M.T., C.S.J., S.G., S.K. and T.M. developed and deployed the software to support proofreading of segmented electron microscopy data. S.D., F.C., C.S.-M. and D.B. deployed and supported the annotation software CAVE. A.W.A., E.L., J.S.P., B.M., L.E., A.M., D.S.S., C.J.D., S.A., S.-Y.J.L., B.P., A.C. and K.S.-K. proofread neurons in FANC and edited the paper. A.S. designed and performed light-microscopy imaging. J.S.P. organized the community guidelines and efforts to proofread and annotate FANC. M.D. and W.-C.A.L. advised the project and edited the paper. A.W.A., E.L. and L.E. analysed data. A.W.A., E.L. and J.C.T. wrote the paper, with input from all other co-authors.

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Correspondence to Wei-Chung Allen Lee or John C. Tuthill .

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Extended data figures and tables

Extended data fig. 1 detailed properties of individual leg and wing mns..

a , Number of input synapses on each leg MN. MNs are ordered by the muscle they innervate, from proximal coxa muscles in the thorax to distal tarsus muscles located in the tibia. b , Number of input synapses on each wing MN. Indirect MNs are shown first, direct MNs are ordered according to sclerite. c , Fraction of synapses on each leg MN broken down by cell class (see  Methods ). d , Fraction of synapses on each wing MN broken down by cell class. e , Number of preMNs presynaptic to each leg MN. f , Number of preMNs presynaptic to each wing MN. g , h , Fraction of presynaptic partners from each cell class. Presynaptic partners include proofread neurons only, so fragments are not included. On average, each MN receives 3,641 input synapses from 188 preMNs (using a 3-synapse threshold) and each preMN synapses onto 6 MNs (7.2 ± 7.4 sd. for leg preMNs, 5.1 ± 3.1 for wing preMNs). i , j , MN volume. k , MN volume vs. surface area for leg MNs (left) and wing MNs (right). Wing MNs tend to have thicker neurites, explaining the steeper relationship. The thick b1 wing steering MN is the outlier.

Extended Data Fig. 2 Agglomerative hierarchical clustering of leg MNs according to premotor connectivity.

a , Hierarchical clustering of MNs based on the cosine similarity of the columns of the premotor connectivity matrix (Fig. 2d ). The scipy.cluster AgglomerativeClustering algorithm minimizes the sum of squared distances in each cluster (Ward, scikit-learn). The algorithm identifies seven clear clusters numbered according to the proximal-to-distal origins and insertion points of the innervated muscles (right). b , Magnification of seven additional clusters at the top left of the similarity matrix. The muscle targets of MNs in each cluster are indicated below. We remain uncertain about which of four MNs innervate the tergopleural vs. the pleural promotor muscles that insert on the anterior aspect of the coxa (cluster 1a). c , In Azevedo et al. 7 , we identified the muscle targets of each MN by comparing anatomical criteria (left). We performed UMAP clustering of the density of input synapses in 3D onto each MN, as an independent, quantitative verification of our anatomical assignments (right). This analysis revealed surprising features that are corroborated by analyzing preMN connectivity here. Specifically, accessory tibia flexor MNs split into 3 distinct clusters, clusters 7, 8, and 9, where the four accessory tibia flexors in cluster 7 clustered with the five main tibia flexor MNs. Additionally, four of the six tarsus MNs clustered with the same groups, one in cluster 7, two in cluster 8, and 1 in cluster 9 (see numbers at bottom). A fifth tarsus MN, the retro depressor MN, clustered on its own (cluster 12). The final tarsus MN clustered with the small LTM MNs in cluster 10; all three are known to express dip-alpha (Venkatasubramanian et al. 75 ). d , Clusters based on premotor connectivity from a and b . The differences from the UMAP of synapse density include: promotor MNs of the coxa (cluster 1a) clustered separately from the adductor and rotator MNs (cluster 1b); the tarsus depressor MN (cluster 13) clustered separately from the two dip-alpha-positive LTM MNs (cluster 10); a small MN clustered in a separate cluster labeled with an asterisk (*), depicted in f . Names for each module are given on the right. e , UMAP embedding of the columns of the premotor connectivity matrix (Fig. 2d ). This clustering does not rely on cosine similarity and largely corroborates the agglomerative clustering. f , Two trochanter flexor MNs with somas on the posterior cortex of the neuropil. In total, six MNs have somas on the dorsal cortex. Four of these neurons innervate the sternal posterior rotator muscle. We argued in Azevedo et al. 7 that the remaining two MNs innervate the trochanter flexor muscle because we observed two axons enter the proximal fibers of the muscle in the X-ray data. The larger of the two MNs (green) clustered with the trochanter flexor MNs according to both the hierarchical clustering and the UMAP embedding. The MN indicated by the asterisk (blue) receives approximately 10X fewer synapses, perhaps explaining why it either clustered by itself ( b ) or with the sternal rotator MNs ( e ). In summary, in the paper, we include the (*) MN with the Trochanter flex MNs.

Extended Data Fig. 3 Similarity of wing MNs creates separable modules through agglomerative clustering.

a , Cosine similarity matrix for all wing MNs. Axes are symmetric, each row/column is an MN. (Right) The agglomerative clustering dendrogram along with the threshold at which clusters are separable. Colored branches on the dendrogram depict different modules, not muscles. b , Similarity scores for each pair of wing MNs. Indirect MNs are separated from direct and tension MNs to better show the distribution of similarity scores of direct and tension MNs. c , Schematic showing how ordering by anatomy (left) relates to agglomerative clustering by cosine similarity (right). d , UMAP does not separate the wing MNs by connectivity, possibly because their synaptic input weights are not stereotyped (or proportional) from preMNs. Data points are colored post-hoc according to the agglomerative clustering results.

Extended Data Fig. 4 Local PreMNs drive MN cosine similarity and modularity, for wing and leg systems.

a , Cumulative density functions (CDFs) of module preference for individual preMNs targeting leg MNs, separated by preMN cell class. Gray indicates ten overlaid example CDFs randomly selected from shuffling the columns of each row of the connectivity matrix. Right, Total MN synapses (y-axis) vs. module preference of local preMNs. Pearson’s r for each cell class is shown, p < 10 −13 . PreMNs with fewer MN synapses have a slight tendency to contact a single module. b , Fraction of MN input synapses (each bar) from local preMNs that prefer that MN’s module (gray) vs. prefer a different module (white). PreMN synapses onto a preferred module account for 62.2% of synapses onto leg MNs. c , Cosine similarity matrices for leg MNs, calculated using synapses from preMNs of each cell class. Modules found in Extended Data Fig. 2 are shown at left and right. Below each matrix is a color bar indicating clusters found by performing the same agglomerative clustering algorithm on the matrix above. Only local preMN connectivity gives the same clusters as using all preMNs. d , CDFs of pairwise similarity of MNs within modules defined in Extended Data Fig. 2 (dark lines) vs. across modules (light colors). Right, the area under the curve (AUC) measures the overlap of the CDFs, with 0.5 indicating similar CDFs, and 1 indicating complete separation (see  Methods ). Gray bars show the improvement in the AUC if the clusters shown below the similarity matrices in c are used instead. Together, these analyses show that local neurons are responsible for the modularity of MNs. Other classes of preMNs tend to prefer a single module ( a ) but can make select synapses across modules. e , Module preference for individual preMNs targeting wing MNs, as in a . f , Fraction of input synapses on wing MNs from local preMNs that preferentially target each MN’s module (gray) vs a different module (white). PreMN synapses onto a preferred module account for 75.7% of synapses onto wing MNs. g , Cosine similarity matrices for indirect (power) MNs, calculated using synapses from preMNs of each cell class. Indirect muscles are divided into two antagonistic modules: dorsal longitudinal muscles (DLMs, dark green) and dorso-ventral muscles (DVMs, light green). They share common input from all cell classes except sensory axons, from which they receive few synapses. h , Pairwise similarity of indirect MNs within modules, based on connectivity of each cell class. i , Similarity matrices for tension and direct (steering) MNs. j , Pairwise similarity of indirect MNs within (dark line) vs. across (light) modules, for each preMN cell class. Colors are indicated in e .

Extended Data Fig. 5 Example leg preMNs, their synapses onto motor modules, and impact of proportional connectivity on MN similarity.

a , The location of synapses (spheres) from example preMNs that preferentially synapse onto the SETi (light orange) and FETi (dark orange) tibia extensor MNs. Each preMN has a different morphology and makes more synapses onto FETi than onto SETi. b , Example preMNs that preferentially synapse onto the five tibia flexor MNs in the Tibia flex A module (different shades of blue spheres). c , A single example preMN from b , showing the locations of synapses onto four of the five tibia flexor MNs in the module. The preMN makes more synapses onto the largest neuron, with extra synapses distributed throughout the processes. d , Bootstrap shuffling of module connectivity (see  Methods for details). This analysis is similar to Fig. 4h , but for only the largest neurons with the highest similarity (green squares), where high MN similarity reflects proportional preMN weights onto each MN in the module, as in a - c . e , Left, the unshuffled synapse counts from all local preMNs onto the Tibia Flex A MNs; middle, the same matrix with example shuffled synapse counts from the module-targeting preMNs; right, the resulting MN similarity matrices, highlighting the pairwise similarities in the upper triangle. f , The cumulative probability density function (cdf) of the mean pairwise MN similarity for N = 10,000 shuffling repeats, compared to the actual mean. The actual mean is larger than 99.7% of the shuffled instances. g , The bootstrap p-value for the regions of high MN similarity. The high p-values indicate pairs of neurons with small differences in their total synaptic input, such that shuffling the proportional synapses does not disrupt a large difference like exists for the FETi and SETi in a .

Extended Data Fig. 6 Leg modules that include biarticular muscles have more variable module connectivity.

a , Principal Components Analysis of the connections between local preMNs and their preferred motor module. Dots and dark gray bars indicate the percent of the module connectivity variance that is explained by a single principal component, for each leg and wing module. The first principal component was sufficient to explain the majority (>80%) of the variance within most leg motor modules. The percentages of variance explained within modules for the wing power MNs were also high (>90%). For both leg modules and the modules of the wing power muscles, the only significant dimension of variation (captured by the first component alone) was simply the overall preMN output onto the modules. By contrast, the first principal component explained only 63%, 55%, 70%, 87%, and 67% of the variance for the tension, steering A, steering B, C and D modules, respectively. This analysis supports our observation that wing module connectivity is not proportional, from Fig. 4h . Here, we further dissect the PCA analysis to show that leg modules that are composed of motor units with more biomechanical diversity have more variable connectivity, in support of our conclusions about the differences between leg and wing connectivity. b , The first principal component for the Trochanter extend module explains less of the variance than for most other leg modules. If the module is separated according to muscle target, the first PC explains more of the variance in the connectivity onto MNs targeting each muscle. c , MNs innervating the sternotrochanter, tergotrochanter, and trochanter extensor muscles. d , Individual traced muscle fibers from the X-ray tomography image volume. The Trochanter extend module contains the biarticular tergotrochanter muscle, which originates at the dorsal thoracic cuticle, crosses the body-coxa joint and extends the trochanter; and the biarticular sternotrochanter muscle, which originates on the ventral thoracic cuticle, crosses the body-coxa joint and extends the trochanter (Azevedo et al. 7 ). Note, we adopted the muscle nomenclature from the literature (Miller, 1950). All three muscles insert on the same tendon, so an alternative naming scheme would call these three parts of the same muscle, like the three parts of the human triceps brachii muscle. e , When MNs innervating the biarticular long tendon muscle (LTM) are separated by anatomy, the first PC explains more of the connectivity onto MNs targeting each muscle. f , Four groups of LTM neurons. The DIP-α LTM MNs are small, lack a medial projection, express DIP-α, and one targets the femur LTM while the other targets the tibia (Venkatasubramanian et al. 75 ). The specific muscle targets of two other smaller LTM MNs are unknown. g , Traced muscle fibers of the LTM. The LTM is composed of two muscles, one in the femur and one in the tibia, that both insert on the long tendon that crosses multiple articulations to insert on the claw at the tip of the tarsus (Radnikow and Bässler, 1991). h , Subdivision of coxa modules, for comparison with biarticular modules. Posterior modules (blue), Anterior modules (orange). Breaking the posterior module into MNs innervating the remotor/abductor muscle or the posterior rotator muscles increases the projection onto the first PC. Excluding a single MN from the coxa promotion module (orange) increases the projection onto the first PC. i , MNs innervating the coxa muscles in the thorax. Black arrowhead indicates the primary neurite of the excluded coxa promotor MN. j , Coxa muscles in the thorax. We are uncertain about how many MNs innervate the tergopleural vs. the pleural promotor muscles, as the axons are not visible in the X-ray tomography images. The excluded promotor MN receives 4,056 total synapses (compared to 1,484, 4,056, and 6,450 for the other promotor MNs) and has high cosine similarity with the rotator and adductor MNs (Extended Data Fig. 4c ). This analysis suggests that the excluded preMN receives input from slightly different sources than the other preMNs. We speculate that perhaps the excluded promotor MN exits the DProN nerve and innervates the pleural promotor, while the others innervate the tergopleural promotor. In short, the leg modules with more variable input, as measured by PCA, include motor units with more complex biomechanics.

Extended Data Fig. 7 Example neurons from each premotor hemilineage.

Example preMNs from each premotor hemilineage. See Supplemental Table 3 for links to view entire premotor populations of each hemilineage in Neuroglancer, an online tool for viewing connectomics datasets.

Supplementary information

Supplementary information.

Supplementary Tables. Supplementary Table 1 contains links for viewing motor neurons organized by motor module in Neuroglancer. Supplementary Table 2 contains links for viewing premotor neurons organized by motor module in Neuroglancer. Supplementary Table 3 contains Neuroglancer links for viewing premotor neurons organized by hemilineage and inferred neurotransmitter.

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Lesser, E., Azevedo, A.W., Phelps, J.S. et al. Synaptic architecture of leg and wing premotor control networks in Drosophila . Nature (2024). https://doi.org/10.1038/s41586-024-07600-z

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