Hypothesis testing is a statistical method used to make decisions based on experimental data. It involves formulating two competing hypotheses: the null hypothesis (H₀) and the alternative hypothesis (H₁). The null hypothesis represents the prevailing belief or status quo, suggesting that there is no effect or difference, while the alternative hypothesis challenges this assumption, indicating that there is an effect or difference ⁵.

The process of hypothesis testing begins with collecting sample data and analyzing it to determine whether there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis. This involves calculating a test statistic and comparing it to a critical value or using a p-value to assess the strength of the evidence against H₀ ¹².

There are various methods for hypothesis testing, including two-tailed tests, lower-tailed tests, and upper-tailed tests. The choice of method depends on the nature of the hypotheses being tested and the data available ⁵. Ultimately, hypothesis testing provides a structured approach to making informed decisions based on statistical evidence.