What is the goal of hypothesis testing?

The goal of hypothesis testing is to determine whether there is enough evidence to reject the null hypothesis in favor of an alternative hypothesis. In hypothesis testing, researchers start by formulating two competing hypotheses: the null hypothesis, which represents a statement of no effect or no difference, and the alternative hypothesis, which represents the opposite—an expectation of some effect or difference.

The process involves collecting and analyzing sample data to compute a test statistic that helps assess the strength of the evidence against the null hypothesis. If the analysis shows that the evidence is statistically significant, researchers will reject the null hypothesis, providing support for the alternative hypothesis. This approach allows researchers to make informed conclusions and decisions based on their data while maintaining a systematic method of validation.

Other options present misunderstandings of the hypothesis testing process. For instance, confirming a theory without any additional data does not align with the scientific method, which requires empirical evidence for validation. Collecting data without specific claims does not reflect the hypothesis testing framework, where specific hypotheses guide the research. Lastly, proving an alternative hypothesis to always be true is unrealistic because hypothesis testing assesses statistical likelihood rather than absolute truth; thus, it allows for the possibility of errors or uncertainties.