This online course provides a comprehensive introduction to hypothesis testing, a fundamental concept in statistical inference. Students will learn the principles and steps involved in formulating and testing hypotheses, including defining null and alternative hypotheses, selecting appropriate test statistics, and determining significance levels (p-values). The course will cover various types of hypothesis tests, such as t-tests, chi-square tests, and ANOVA, along with their applications. Through interactive lessons, real-world examples, and hands-on exercises, participants will gain the skills to conduct hypothesis tests, interpret results, and make data-driven decisions with confidence.