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- How to Write a Strong Hypothesis | Steps & Examples
How to Write a Strong Hypothesis | Steps & Examples
Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.
A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection .
Example: Hypothesis
Daily apple consumption leads to fewer doctor’s visits.
Table of contents
What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, frequently asked questions about writing hypotheses.
A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.
A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).
Variables in hypotheses
Hypotheses propose a relationship between two or more types of variables .
- An independent variable is something the researcher changes or controls.
- A dependent variable is something the researcher observes and measures.
If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias will affect your results.
In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .
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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.
Step 2. Do some preliminary research
Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.
At this stage, you might construct a conceptual framework to ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize more complex constructs.
Step 3. Formulate your hypothesis
Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.
4. Refine your hypothesis
You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:
- The relevant variables
- The specific group being studied
- The predicted outcome of the experiment or analysis
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.
In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.
If you are comparing two groups, the hypothesis can state what difference you expect to find between them.
6. Write a null hypothesis
If your research involves statistical hypothesis testing , you will also have to write a null hypothesis . The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .
- H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
- H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.
| Research question | Hypothesis | Null hypothesis |
|---|---|---|
| What are the health benefits of eating an apple a day? | Increasing apple consumption in over-60s will result in decreasing frequency of doctor’s visits. | Increasing apple consumption in over-60s will have no effect on frequency of doctor’s visits. |
| Which airlines have the most delays? | Low-cost airlines are more likely to have delays than premium airlines. | Low-cost and premium airlines are equally likely to have delays. |
| Can flexible work arrangements improve job satisfaction? | Employees who have flexible working hours will report greater job satisfaction than employees who work fixed hours. | There is no relationship between working hour flexibility and job satisfaction. |
| How effective is high school sex education at reducing teen pregnancies? | Teenagers who received sex education lessons throughout high school will have lower rates of unplanned pregnancy teenagers who did not receive any sex education. | High school sex education has no effect on teen pregnancy rates. |
| What effect does daily use of social media have on the attention span of under-16s? | There is a negative between time spent on social media and attention span in under-16s. | There is no relationship between social media use and attention span in under-16s. |
If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.
- Sampling methods
- Simple random sampling
- Stratified sampling
- Cluster sampling
- Likert scales
- Reproducibility
Statistics
- Null hypothesis
- Statistical power
- Probability distribution
- Effect size
- Poisson distribution
Research bias
- Optimism bias
- Cognitive bias
- Implicit bias
- Hawthorne effect
- Anchoring bias
- Explicit bias
A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).
Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
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without restricting hypothesis class - over tting ERM algorithm learns nite hypothesis classes (examples: apple factory ( nite-precision rectangles), conjunctions) Agnostic learning in the statistical model Agnostic learning as a way for handling noise (HW1) Started in nite learnable hypothesis classes: half-lines, rectangles.
Hypothesis classes also don't have to consist of only simple functions. If you manage to search over all piecewise-$\tanh^2$ functions, then those functions are what your hypothesis class includes. The big tradeoff is that the larger your hypothesis class, the better the best hypothesis models the underlying true function, but the harder it is ...
5. This is a followup to the answers here and here. I have not seen this term in any textbooks I have or many online resources. It is not, for example, present on the SVM wikipedia page. What is a hypothesis class in the context of SVM? How do the support vectors relate to the hypothesis class (es)? svm. Share. Cite.
To handle the difference between empirical and expected losses . Choose large margin hypothesis (high confidence) . Choose a small hypothesis class. ෝ ∗. Corresponds to the hypothesis class. Thought experiment. Principle: use smallest hypothesis class still with a correct/good one. Also true beyond SVM.
A hypothesis is a function that best describes the target in supervised machine learning. The hypothesis that an algorithm would come up depends upon the data and also depends upon the restrictions and bias that we have imposed on the data. The Hypothesis can be calculated as: y = mx + b y =mx+b. Where, y = range. m = slope of the lines.
As an example for a class with uniform convergence property, we consider finite classes. The next claim is a direct corollary of Claim. 2.4: Example 2.3. A finite Hypothesis class has the uniform convergence property. In the next lecture we will define the VC dimension.
The hypothesis is one of the commonly used concepts of statistics in Machine Learning. It is specifically used in Supervised Machine learning, where an ML model learns a function that best maps the input to corresponding outputs with the help of an available dataset. In supervised learning techniques, the main aim is to determine the possible ...
2.1 Learning a Class from Examples 23 x 2: Engine power x 1: Price p 1 p 2 e 1 e 2 C Figure 2.2 Example of a hypothesis class. The class of family car is a rectangle in the price-engine power space. Our training data can now be plotted in the two-dimensional (x1,x2) space where each instance t is a data point at coordinates (xt 1,x t 2) and its
A concept class C is a set of true functions f.Hypothesis class H is the set of candidates to formulate as the final output of a learning algorithm to well approximate the true function f.Hypothesis class H is chosen before seeing the data (training process).C and H can be either same or not and we can treat them independently.
A hypothesis is an explanation for something. It is a provisional idea, an educated guess that requires some evaluation. A good hypothesis is testable; it can be either true or false. In science, a hypothesis must be falsifiable, meaning that there exists a test whose outcome could mean that the hypothesis is not true.
This course introduces principles, algorithms, and applications of machine learning from the point of view of modeling and prediction. It includes formulation of learning problems and concepts of representation, over-fitting, and generalization. These concepts are exercised in supervised learning and reinforcement learning, with applications to images and to temporal sequences.
For example, everything_except(int) returns a strategy that can generate anything that from_type() can ever generate, except for instances of int, and excluding instances of types added via register_type_strategy(). This is useful when writing tests which check that invalid input is rejected in a certain way. hypothesis.strategies. frozensets (elements, *, min_size = 0, max_size = None ...
There are 5 main steps in hypothesis testing: State your research hypothesis as a null hypothesis and alternate hypothesis (H o) and (H a or H 1 ). Collect data in a way designed to test the hypothesis. Perform an appropriate statistical test. Decide whether to reject or fail to reject your null hypothesis. Present the findings in your results ...
Here are some research hypothesis examples: If you leave the lights on, then it takes longer for people to fall asleep. If you refrigerate apples, they last longer before going bad. If you keep the curtains closed, then you need less electricity to heat or cool the house (the electric bill is lower). If you leave a bucket of water uncovered ...
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 ...
The definition of VC-dimension applies to all types of hypothesis classes. Example 1.5 (binary decision trees). Let Hbe the set of decision trees of size 3 (depth 3) on nvariables. A single hypothesis h 2Hcan fully represent functions on 3 of the nvariables, but no more, so VC-dimension(H)=3. Example 1.6 (infinite VC-dimension).
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.
Ok so I found an answer, its turns out it is really simple you can use the from_type generator from_type documentation. In the simple example I described above one could do something like. from hypothesis import given. from hypothesis.strategies import from_type. @dataclass(frozen=True) class SensorModel:
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 ...
Examples of Hypothesis. Here are a few examples of hypotheses in different fields: Psychology: "Increased exposure to violent video games leads to increased aggressive behavior in adolescents.". Biology: "Higher levels of carbon dioxide in the atmosphere will lead to increased plant growth.".
1. Hypothesis (h): A Hypothesis can be a single model that maps features to the target, however, may be the result/metrics. A hypothesis is signified by "h". 2. Hypothesis Space (H): A Hypothesis space is a complete range of models and their possible parameters that can be used to model the data. It is signified by "H".
Hypothesis Testing Examples. We know it can be hard to write a good hypothesis unless you've seen some good hypothesis examples. We've included four hypothesis examples based on some made-up experiments. Use these as templates or launch pads for coming up with your own hypotheses. Experiment #1: Students Studying Outside (Writing a Hypothesis)
The hypothesis is often written using the words "IF" and "THEN." For example, "If I do not study, then I will fail the test." The "if' and "then" statements reflect your independent and dependent variables. The hypothesis should relate back to your original question and must be testable.
The researchers write their hypotheses. These statements apply to the population, so they use the mu (μ) symbol for the population mean parameter.. Null Hypothesis (H 0): The population means of the test scores for the two groups are equal (μ 1 = μ 2).; Alternative Hypothesis (H A): The population means of the test scores for the two groups are unequal (μ 1 ≠ μ 2).