Hypothesis testing can be an overwhelming topic to grasp if you’re new to the subject. As well as dealing with all of the different terminology, you have to perform several steps to run a test. Even if you use software, you have decisions to make at each step, such as what you’re testing in the first place and what kind of wiggle room for error you’re willing to accept. This graphic gives an overview of the hypothesis testing process in one picture. See below for links to articles explaining each part of the procedure in more detail.
More info:
Null Hypothesis Definition and Examples, How to State
Alternate Hypothesis in Statistics: What is it?
Alpha Level (Significance Level): What is it?
Type I and II errors.
Data Collection Methods
Test Statistics
Which statistical test to choose?
References
Average Data Scientist Salary (Glassdoor)
Credit: Data Science Central By: Stephanie Glen
