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Hypothesis is a testable statement that explains what is happening or observed. It proposes the relation between the various participating variables. Hypothesis is also called Theory, Thesis, Guess, Assumption, or Suggestion. Hypothesis creates a structure that guides the search for knowledge.
In this article, we will learn what is hypothesis, its characteristics, types, and examples. We will also learn how hypothesis helps in scientific research.
Table of Content
Hypothesis meaning, characteristics of hypothesis, sources of hypothesis, types of hypothesis, simple hypothesis, complex hypothesis, directional hypothesis, non-directional hypothesis, null hypothesis (h0), alternative hypothesis (h1 or ha), statistical hypothesis, research hypothesis, associative hypothesis, causal hypothesis, hypothesis examples, simple hypothesis example, complex hypothesis example, directional hypothesis example, non-directional hypothesis example, alternative hypothesis (ha), functions of hypothesis, how hypothesis help in scientific research.
A hypothesis is a suggested idea or plan that has little proof, meant to lead to more study. It’s mainly a smart guess or suggested answer to a problem that can be checked through study and trial. In science work, we make guesses called hypotheses to try and figure out what will happen in tests or watching. These are not sure things but rather ideas that can be proved or disproved based on real-life proofs. A good theory is clear and can be tested and found wrong if the proof doesn’t support it.
A hypothesis is a proposed statement that is testable and is given for something that happens or observed.
Here are some key characteristics of a hypothesis:
Hypotheses can come from different places based on what you’re studying and the kind of research. Here are some common sources from which hypotheses may originate:
Here are some common types of hypotheses:
Simple Hypothesis guesses a connection between two things. It says that there is a connection or difference between variables, but it doesn’t tell us which way the relationship goes.
Complex Hypothesis tells us what will happen when more than two things are connected. It looks at how different things interact and may be linked together.
Directional Hypothesis says how one thing is related to another. For example, it guesses that one thing will help or hurt another thing.
Non-Directional Hypothesis are the one that don’t say how the relationship between things will be. They just say that there is a connection, without telling which way it goes.
Null hypothesis is a statement that says there’s no connection or difference between different things. It implies that any seen impacts are because of luck or random changes in the information.
Alternative Hypothesis is different from the null hypothesis and shows that there’s a big connection or gap between variables. Scientists want to say no to the null hypothesis and choose the alternative one.
Statistical Hypotheis are used in math testing and include making ideas about what groups or bits of them look like. You aim to get information or test certain things using these top-level, common words only.
Research Hypothesis comes from the research question and tells what link is expected between things or factors. It leads the study and chooses where to look more closely.
Associative Hypotheis guesses that there is a link or connection between things without really saying it caused them. It means that when one thing changes, it is connected to another thing changing.
Causal Hypothesis are different from other ideas because they say that one thing causes another. This means there’s a cause and effect relationship between variables involved in the situation. They say that when one thing changes, it directly makes another thing change.
Following are the examples of hypotheses based on their types:
Hypotheses have many important jobs in the process of scientific research. Here are the key functions of hypotheses:
Researchers use hypotheses to put down their thoughts directing how the experiment would take place. Following are the steps that are involved in the scientific method:
Mathematics Maths Formulas Branches of Mathematics
A hypothesis is a testable statement serving as an initial explanation for phenomena, based on observations, theories, or existing knowledge. It acts as a guiding light for scientific research, proposing potential relationships between variables that can be empirically tested through experiments and observations.
The hypothesis must be specific, testable, falsifiable, and grounded in prior research or observation, laying out a predictive, if-then scenario that details a cause-and-effect relationship. It originates from various sources including existing theories, observations, previous research, and even personal curiosity, leading to different types, such as simple, complex, directional, non-directional, null, and alternative hypotheses, each serving distinct roles in research methodology .
The hypothesis not only guides the research process by shaping objectives and designing experiments but also facilitates objective analysis and interpretation of data , ultimately driving scientific progress through a cycle of testing, validation, and refinement.
What is a hypothesis.
A guess is a possible explanation or forecast that can be checked by doing research and experiments.
The components of a Hypothesis are Independent Variable, Dependent Variable, Relationship between Variables, Directionality etc.
Testability, Falsifiability, Clarity and Precision, Relevance are some parameters that makes a Good Hypothesis
You cannot prove conclusively that most hypotheses are true because it’s generally impossible to examine all possible cases for exceptions that would disprove them.
Hypothesis testing is used to assess the plausibility of a hypothesis by using sample data
Yes, you can change or improve your ideas based on new information discovered during the research process.
Hypotheses are used to support scientific research and bring about advancements in knowledge.
Similar reads.
We have heard of many hypotheses which have led to great inventions in science. Assumptions that are made on the basis of some evidence are known as hypotheses. In this article, let us learn in detail about the hypothesis and the type of hypothesis with examples.
A hypothesis is an assumption that is made based on some evidence. This is the initial point of any investigation that translates the research questions into predictions. It includes components like variables, population and the relation between the variables. A research hypothesis is a hypothesis that is used to test the relationship between two or more variables.
Following are the characteristics of the hypothesis:
Following are the sources of hypothesis:
There are six forms of hypothesis and they are:
It shows a relationship between one dependent variable and a single independent variable. For example – If you eat more vegetables, you will lose weight faster. Here, eating more vegetables is an independent variable, while losing weight is the dependent variable.
It shows the relationship between two or more dependent variables and two or more independent variables. Eating more vegetables and fruits leads to weight loss, glowing skin, and reduces the risk of many diseases such as heart disease.
It shows how a researcher is intellectual and committed to a particular outcome. The relationship between the variables can also predict its nature. For example- children aged four years eating proper food over a five-year period are having higher IQ levels than children not having a proper meal. This shows the effect and direction of the effect.
It is used when there is no theory involved. It is a statement that a relationship exists between two variables, without predicting the exact nature (direction) of the relationship.
It provides a statement which is contrary to the hypothesis. It’s a negative statement, and there is no relationship between independent and dependent variables. The symbol is denoted by “H O ”.
Associative hypothesis occurs when there is a change in one variable resulting in a change in the other variable. Whereas, the causal hypothesis proposes a cause and effect interaction between two or more variables.
Following are the examples of hypotheses based on their types:
Following are the functions performed by the hypothesis:
Researchers use hypotheses to put down their thoughts directing how the experiment would take place. Following are the steps that are involved in the scientific method:
What is hypothesis.
A hypothesis is an assumption made based on some evidence.
What are the types of hypothesis.
Types of hypothesis are:
Define complex hypothesis..
A complex hypothesis shows the relationship between two or more dependent variables and two or more independent variables.
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2024 Theses Doctoral
Segura, Luis Esteban
A groundbreaking narrative, which would come to be known as the theory of “deaths of despair”, emerged in 2015 from a study by Case and Deaton analyzing mortality rates in the United States between 1999 and 2013. They found an increasing trend in all-cause mortality rates due to drug poisonings, alcohol-related liver disease, and suicides, which they called “deaths of despair”, among non-Hispanic (NH) white Americans aged 45 to 54—this age group was called the midlife. Case and Deaton’s findings and their narrative about the hypothetical causes of their findings garnered significant attention. The authors of this narrative hypothesized that the observed increases in mortality rates were due to white individuals in midlife increasingly suffering from “despair” and proposed a causal link between increasing “despair” rates and increased mortality rates only among white Americans in midlife. Case and Deaton did not provide a clear definition of “despair”; they presumed that white Americans in midlife were hopeless about their prospects for the future compared to what their parents had attained. This provocative narrative persisted and gained momentum because it functioned as an explanation of recent events like the 2016 U.S. presidential election, rise in white nationalism, and far right extremism. These white-related events were thought to be expressions of an agonizing, poor, under-educated generation of white Americans increasingly suffering from hypothetical feelings of "despair”, which have led them to self-destructive behaviors and premature death. However, no study has investigated the central claim of this theory: whether there is evidence of an association between increased “despair” rates and increased mortality rates only among white individuals in midlife, particularly for those with low education. Moreover, there is little evidence of their hypothesis of an increasing epidemic of “despair” affecting only white Americans in midlife, particularly those with low education. The theory of “deaths of despair” can be understood through Geoffrey Rose’s framework of causes of incidence and causes of cases, which highlights the difference between between-population and inter-individual causes of disease. Rose’s argues that causes of incidence explain the changes in outcome rates between populations, and may be uniform and imperceptible within populations. On the other hand, the causes of cases explain why some individuals within a population are susceptible or at high risk of the outcome. Like Rose’s causes of incidence, the authors of the theory of “deaths of despair” argue that “despair” increased between the midlife white American population in 1999 and in 2014, which led to increased mortality rates. Conversely, this theory does not claim that some individuals are at higher risk of death due to “despair”, which would be analogous to causes of cases. Therefore, the contrast of interest to test the central claim of Case and Deaton’s theory of “deaths of despair” is a between-population contrast (causes of incidence). As such, this dissertation aims to test the claims of the theory of “deaths of despair” proposed by Case and Deaton at the right level (causes of incidence). I began by conducting a scoping review of the current literature providing empirical support to the different elements of this theory: 1) socioeconomic causes as causes of “despair”, “diseases of despair”, “deaths of despair”, and all-cause mortality, and 2) “despair” as the cause of “diseases of despair”, “deaths of despair”, and all-cause mortality. I found 43 studies that I organized and displayed in two graphs according to Rose’s causes of cases (individual-level causes of “deaths of despair”) and causes of incidence (between-population level causes of “deaths of despair” rates). In each graph, I showed the number of studies that provided evidence for the individual- or population-level elements of the theory of “deaths of despair”. Of these 43 studies, I found that only 13 studies explicitly stated that they tested this theory. Three studies provided different definitions of “despair”, which did not align with the previous vague definition provided by Case and Deaton about white individuals’ hopeless about their prospects for the future. Most studies provided individual-level evidence for “despair” increasing the likelihood of death and despair-related outcomes, which is analogous to a type III error—a mismatch between the research question and the level at which the studies’ design and analyses were conducted to answer that question. Further, no study addressed at the right level—between populations—the central claim of the theory of “deaths of despair”. This led me to review the literature around concepts similar to “despair” and propose a suitable indicator to test the claims of the theory of “deaths of despair”. I leveraged data from the National Health Interview Survey and the Centers for Disease Control mortality data to test whether increases in the prevalence of “despair” were associated with increases in all-cause mortality rates only among white individuals in midlife and whether this effect was bigger among low educated white individuals. To obtain a valid estimate of this association, I adapted econometric methods to develop a valid estimator of the association between increasing “despair” prevalence and increased all-cause mortality rates. After adjusting for potential confounders at the between-population level, I found that the trends in the prevalence of “despair” were negligible across all race and ethnic groups and that an increasing trend could not be identified. Further, I found no evidence that increasing prevalences of “despair” were associated with increased all-cause mortality rates among NH white individuals in midlife, or that this association was more pronounced for those with low education. Lastly, I conducted a similar analysis looking at the association between increased prevalences of “despair” and increased rates of “deaths of despair”. I replicated Case and Deaton’s observed increased rates of “deaths of despair” among white individuals in midlife. However, I found no evidence that increased prevalences of “despair” were associated with increased “deaths of despair” rates among white individuals in midlife or that this association was higher for those with low education. Together, these findings suggest that the claims about the causes of increased mortality rates among white Americans in midlife are at best, questionable, and at worst, false. My aim with this work is to challenge and provide a critical examination of the theory of "deaths of despair", which has fueled the narrative of a suffering white generation and justified recent problematic events as white individuals lashing out for being forgotten to despair and die. While Case and Deaton’s observed rise in mortality rates among whites is a reproducible fact, their narrative ignores other evidence of white racial resentment as the cause of rise in mortality among white individuals. With this work, I intend to help stopping the perpetuation of narratives that favor structural whiteness by promoting an unsubstantiated narrative of psychosocial harm experienced by white Americans. Ultimately, I hope this work helps shift the focus in public health away from Case and Deaton's findings, which may overshadow and detract from the stark reality that mortality rates for Black individuals significantly exceed those for white individuals.
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Developing a hypothesis (with example) Step 1. Ask a question. Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project. Example: Research question.
Hypothesis. Definition: Hypothesis is an educated guess or proposed explanation for a phenomenon, based on some initial observations or data. It is a tentative statement that can be tested and potentially proven or disproven through further investigation and experimentation. ... After formulating the hypothesis, it's important to refine it ...
A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process. Consider a study designed to examine the relationship between sleep deprivation and test ...
A hypothesis is a prediction of what will be found at the outcome of a research project and is typically focused on the relationship between two different variables studied in the research. It is usually based on both theoretical expectations about how things work and already existing scientific evidence. Within social science, a hypothesis can ...
Formulating a hypothesis involves identifying research questions, conducting preliminary research, and crafting a clear and precise statement. A strong hypothesis is characterized by its testability, clarity, precision, and relevance to the research objectives. Common pitfalls in hypothesis writing include vague statements, overly complex ...
Scientific hypothesis is an idea that tries to explain a natural phenomenon based on observation or experimentation. Learn how to formulate and test a scientific hypothesis, and what makes it different from other types of hypotheses, with examples from various fields of science.
What is a Hypothesis / Definition. A hypothesis is like a bet: you size things up and tell your mates exactly what you think is going to happen with respect to X, Y, Z. ... Formulate the Hypothesis; Based on your research question and preliminary research, now you can create your hypothesis. A good hypothesis should be clear, concise, and testable.
Simple hypothesis. A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, "Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking. 4.
Step 5: Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable. If a first-year student starts attending more lectures, then their exam scores will improve.
It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis. 7.
The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem. 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a 'if-then' structure. 3.
A good research hypothesis is informed by prior research and guides research design and data analysis, so it is important to understand how a hypothesis is defined and understood by researchers. What is the simple definition of a hypothesis? A hypothesis is a testable prediction about an outcome between two or more variables. It functions as a ...
A research hypothesis (or scientific hypothesis) is a statement about an expected relationship between variables, or explanation of an occurrence, that is clear, specific and testable. So, when you write up hypotheses for your dissertation or thesis, make sure that they meet all these criteria. If you do, you'll not only have rock-solid ...
The hypothesis is a predictive, testable statement predicting the outcome and the results the researcher expects to find. The hypothesis provides a summary of what direction, if any, is taken to investigate a theory. In scientific research, there is a criterion that hypotheses need to be met to be regarded as acceptable.
A research hypothesis, in its plural form "hypotheses," is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.
Hypothesis testing example. You want to test whether there is a relationship between gender and height. Based on your knowledge of human physiology, you formulate a hypothesis that men are, on average, taller than women. To test this hypothesis, you restate it as: H 0: Men are, on average, not taller than women. H a: Men are, on average, taller ...
1. Select a topic. Pick a topic that interests you, and that you think it would be good to know more about. [2] If you are writing a hypothesis for a school assignment, this step may be taken care of for you. 2. Read existing research. Gather all the information you can about the topic you've selected.
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.
To formulate a hypothesis, a researcher must consider the requirements of a strong hypothesis: Make a prediction based on previous observations or research. Define objective independent and ...
The researcher states a hypothesis to be tested, formulates an analysis plan, analyzes sample data. according to the plan, and accepts or rejects the null hypothesis, based on r esults of the ...
Hypothesis Meaning. A hypothesis is a proposed statement that is testable and is given for something that happens or observed. ... Formulating Research Questions: Research questions often create guesses. They assist in changing big questions into particular, checkable things. They guide what the study should be focused on.
Functions of Hypothesis. Following are the functions performed by the hypothesis: Hypothesis helps in making an observation and experiments possible. It becomes the start point for the investigation. Hypothesis helps in verifying the observations. It helps in directing the inquiries in the right direction.
A groundbreaking narrative, which would come to be known as the theory of "deaths of despair", emerged in 2015 from a study by Case and Deaton analyzing mortality rates in the United States between 1999 and 2013. They found an increasing trend in all-cause mortality rates due to drug poisonings, alcohol-related liver disease, and suicides, which they called "deaths of despair", among ...