What does hypothesis testing involve?

Hypothesis testing is a statistical method used to make decisions or inferences about population parameters based on sample data. It involves taking a specific, testable statement about a population—known as a hypothesis—and using inferential statistics to assess whether the evidence from the sample data supports or contradicts this hypothesis.

This process typically includes formulating a null hypothesis, which is a statement of no effect or no difference, and an alternative hypothesis that represents what you aim to prove. After gathering data and performing statistical tests, results are analyzed to determine whether the null hypothesis can be rejected in favor of the alternative. The goal is to provide a systematic way to evaluate evidence, allowing researchers to draw conclusions based on data rather than assumptions or conjecture.

The other options do not accurately describe hypothesis testing: examining qualitative data for insights focuses more on exploratory research rather than testing specific hypotheses, gathering data without any structured approach lacks the rigor of hypothesis testing, and generating new theories without prior evidence does not align with the structured methodology that hypothesis testing employs, as it relies on existing data to draw conclusions.