Identification of the input and output variable of interest; Types of tests to for various combinations of Y and X; Flow path to determine the test to be conducted based on the input and output parameters; Parametric tests for normal data and non parametric tests for non normal data; Understanding the business problem; Identifying the inputs and output variables of interest in the case study and choosing the appropriate test;

Formulating the Null and the alternate hypothesis for normality test; Choice of null hypothesis based on absence of action and the vice versa for alternate hypothesis; checking for normality in Minitab; interpreting the Q–Q plot; Comparing the computed ‘p’ value with α (alpha) for taking the decision on whether or not to take the action; Step to performing the 1 sample Z test, selection of appropriate hypothesis in minitab. Formulation of the conclusion statement at the end of the test

Perform check test on data for normality; selection of the appropriate test to be conducted based on conditions of data;

Performing Non parametric test for non normal data; 1 sample Sign test for one sample using population median measure

Understanding what external conditions are, in an experiment; identifying the existence of external conditions given various scenarios

Defining the Null and Alternate hypothesis statements for the given case study; defining the Ho and Ha for the various comparative tests that are a part of the t - test, Using minitab.

Conducting the comparative tests viz Normality test, Equal variance test using Minitab

Learn the hypothesis statements for 2 sample t - test and the 2 sample t - test using minitab, Iterative hypothesis testing

Formulating the null and the alternate hypothesis statements based on the test flowpath; conduct of Normality test for all samples

Learn how to conduct Normality test for all samples, Variance test for more than 2 populations

Formulation of Null and alternate hypothesis statement for ANOVA test for comparisons; Conduct of one way ANOVA using Minitab.

The distinction between one way ANOVA, Two Way ANOVA and Multiple ANOVA or MANOVA.

Application of 2 proportion test based on the output & input data types; Formulating the hypothesis statements; Iterative testing of 2 proportion test

Understanding the business problem, Identifying the Y and X and their data types; Choosing the appropriate tests based on the flow path diagram; Perform Normality test using ‘graphical summary’ option in Minitab; Performing one way Anova and reconciling the results with the Hypothesis statement;

Selecting all the possible graphical outputs in Minitab for analysis; Using Tukey test for comparisons of means; Interpreting the Tukey pair wise comparison based on ‘letter’ sharing method; Interpreting residual plots, Interval plot, Individual plot and box plot, Inferring the sample with the highest mean and lowest mean based on the difference measures

Recap of the various types of tests based on the data types of X and Y, understand the purpose of using hypothesis testing for predictive analytics

Choosing correct test based on the number of inputs; Formulating the combined Hypothesis statement for Null and Alternate; Conducting the Chi Square Test using minitab

Perform the check for normality test for 2 samples; choosing the non – parametric test of comparisons of medians when the data is found to be not normal

Checking for normality test; performing the paired T test when the external conditions are the same; formulating the Null and the alternative hypothesis statements;

Understanding the logic behind the mood’s median test; Mood’s Median Vs Kruskal Wallis where to use; Performing both the tests and comparing the results;