Hypothesis testing is a statistical method used to make decisions about a population parameter based on sample data. It involves formulating two competing hypotheses: the null hypothesis (H0) and the alternative hypothesis (H1). The null hypothesis represents a default position that there is no effect or difference, while the alternative hypothesis suggests that there is an effect or difference¹².

Key Principles

Null and Alternative Hypotheses

• Null Hypothesis (H0): Assumes no effect or difference. For example, H0: μ = 170 cm (the average height of people in Denmark is 170 cm).

• Alternative Hypothesis (H1): Suggests an effect or difference. For example, H1: μ > 170 cm (the average height of people in Denmark is more than 170 cm)².

Significance Level (α)

The significance level, often denoted by alpha (α), is the probability of rejecting the null hypothesis when it is true. Common choices for α are 0.05 (5%), 0.01 (1%), and 0.10 (10%)¹³.

Test Statistic