Research Question

CategoriesCausal Inference , Study Design , Causal Effect

The research question is the problem or phenomenon being investigated, while the hypotheses are proposed explanations or predictions for the observed phenomenon.

In experimental design, a research question is a statement that identifies the problem or phenomenon that the researcher wants to investigate. It typically involves formulating a clear and concise question that can be answered through a systematic and controlled study.

A good research question should be specific, measurable, achievable, relevant, and time-bound (SMART). It should guide the researcher in designing a study that will generate data to help answer the question.

For example, a research question in experimental design might be, "Does consuming caffeine before an exam improve test performance among college students?" This question is specific, measurable (test performance), achievable (caffeine can be administered and test scores can be measured), relevant to college students, and time-bound (the study can be conducted during a specific time frame).

Overall, the research question serves as the foundation for experimental design and helps to ensure that the study is focused and meaningful.

The Hypothesis

A key part of the research question is the hypothesis. A hypothesis is a proposed explanation or prediction for an observed phenomenon or problem. It is a tentative statement that can be tested through empirical data and analysis. In other words, a hypothesis is a statement that proposes a relationship between variables and makes a prediction about how they will behave in a study.

There are two types of hypotheses in experimental design: the null hypothesis and the alternative hypothesis.

  1. Null Hypothesis (H0): The null hypothesis proposes that there is no significant relationship between the variables being studied. It is the default hypothesis and assumes that any observed differences are due to chance or random error.

For example, in a study investigating the effect of caffeine on test performance among college students, the null hypothesis might be that "there is no significant difference in test performance between students who consume caffeine and those who do not."

  1. Alternative Hypothesis (H1): The alternative hypothesis might propose that there is a significant relationship between the variables being studied. It is the opposite of the null hypothesis and suggests that any observed differences are not due to chance.

Using the same example as before, the alternative hypothesis might be that "students who consume caffeine will perform significantly better on tests than students who do not."

In experimental design, the goal is to collect and analyze data to either support or reject the null hypothesis in favor of the alternative hypothesis. This helps to draw meaningful conclusions about the relationship between variables and inform future research in the field.

Causal research questions

Having a good idea of the research question will help you to develop causal research questions and explore these potential causal effects using experiments. The most widely accepted type of experiment to prove causality is the randomized controlled trial (RCT). However, it is also possible to prove causality using observational data and causal inference

From research question to data, and domain knowledge

Your research question will lead you to your hypotheses, and your hypotheses will help you identify the data you need to collect to conduct your experiment. 

From there, the next step is to begin using Causal Wizard and provide your domain knowledge to define the problem Causal Wizard will solve for you.

 

 

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