• Hypothesis testing requires sample data to draw conclusions about the characteristics of the underlying population that we call parameters, such as the mean \(\mu\), the variance \(\sigma^2\) or standard deviation \(\sigma\)

  • Not only the parameters from a single population, but the equality of the parameters of two or more different populations can be tested

  • For example, we can use hypothesis testing on the following statements to determine whether they are true:

The average age of the population of a certain coutry is above 30

The variance of the portfolio returns is 10 percent

The average working hours per week are equal between two cities

The length of the average flight delay is the same at two airports