<p><strong>The world produces more data than ever. Are you ready for it?</strong></p><p><br></p><p>In today's data-driven world, you hear about making decisions based on data all the time. Hypothesis testing plays a crucial role in that process, whether you're in academia, business, or data science. Without hypothesis tests, you risk making bad decisions.</p><p><br></p><p><strong>Chances are high you'll need to understand these tests to analyze your data and evaluate the work of others.</strong></p><p><br></p><p>Build the knowledge for effective hypothesis testing! Know when to use each test, how to use them reliably, and how to interpret the results correctly!</p><p><br></p><ul><li>Understand why you need hypothesis tests and how they work.</li><li>Effectively use significance levels, p-values, confidence intervals.</li><li>Select the correct type of test to answer your question.</li><li>Learn how to test means, medians, variances, proportions, distributions, counts, correlations for continuous and categorical data, and find outliers.</li><li>One-Way ANOVA, Two-Way ANOVA, and interaction effects.</li><li>Check assumptions to obtain reliable results.</li><li>Manage the error rates for false positives and false negatives.</li><li>Understand sampling distributions, the central limit theorem, and statistical power.</li><li>Know how t-tests, F-tests, chi-squared, and post hoc tests work.</li><li>Learn about differences between parametric, nonparametric, and bootstrapping methods.</li><li>Examples of many hypothesis tests.</li><li>Access free downloadable datasets so you can try it yourself.</li></ul>