Hypothesis testing involves applying different tests on samples and derive inferences which can be applied for the entire population.The general structure of hypothesis testing is as follows- SAMPLE DATA -->> Experiments(T test, Ftest, Ztest,Chisquare test etc) ---> Decision (hypothesis stated,applied for the entire population. This module discusses different tests (Ttest,ChiSquare and Annova Test) and their significance in hypothesis testing(using sample statistics to generate inference about population parameters).

Steps for hypothesis testing - Step 1) State null and alternative hypothesis Step 2) Determine significance value(threshold p value for required for validating null hypothesis) or plot rejection region on a standard normal distribution plot by calculating the statistic(Zscore,Tvalue,Chisquare value etc) Step 3) Determine p value /given statistic of the sample under consideration using different experiments. Step 4) State decision rule (for accepting/rejecting null hypothesis).