Hypothesis testing is a formal way of checking if a hypothesis about a population is true or not.
A hypothesis is a claim about a population parameter. A hypothesis test is a formal procedure to check if a hypothesis is true or not.
Example Claims:
Hypothesis testing is based on making two different claims about a population parameter:
Null Hypothesis (H0): The claim that there is no effect or no difference.
Alternative Hypothesis (Ha): The claim we want to prove.
Example: “The average height of people in Denmark is more than 170 cm.”
The significance level (α) is the uncertainty we accept when rejecting the null hypothesis. Typical significance levels are:
Note: A 5% significance level means that when we reject a null hypothesis, we expect to reject a true null hypothesis 5 out of 100 times.
The test statistic is a standardized value calculated from the sample. It helps decide the outcome of the hypothesis test.
Common Distributions:
Two approaches for hypothesis testing:
