A hypothesis is a proposed explanation or assumption about a population parameter that serves as the basis for testing and analysis.

The null hypothesis, or H₀, assumes no significant difference or relationship between the variables under study. In contrast, the alternative hypothesis, or H₁, suggests a significant difference or relationship between the studied variables.

Statistical significance is tested to check the acceptance of either hypothesis with substantial evidence to support the claim.

Hypothesis testing is vital in making informed decisions based on data and determining if adequate evidence supports or refutes a hypothesis.

For instance, it assesses a new drug's effectiveness by comparing the treatment and control groups.

It can also elucidate relationships, such as the correlation between smoking and lung cancer, or gauge the impact of strategies, like marketing campaigns, on sales.

Lastly, it can measure satisfaction differences, such as by examining customer responses to different product versions.