Hypothesis testing is a critical tool in inferential statistics, for determing what the value of a population parameter could be. We often draw this conclusion based on a sample data analysis.
The basis of hypothesis testing has two attributes:
Null Hypothesis: ๐ป0 Alternative Hypothesis: ๐ป๐ The tests we will discuss in this notebook are:
One Population Proportion Difference in Population Proportions One Population Mean Difference in Population Means In this notebook, we will also introduce some functions (from the statsmodels Python package) that are extremely useful when calculating a t-statistic, or a z-statistic, and corresponding p-values for a hypothesis test.
Let's quickly review the following ways to calculate a test statistic for the tests listed above.