Data Science - Hypothesis Testing using Minitab, R is designed to cover majority of the capabilities from Analytics & Data Science perspective, which includes the following:
Describes about course content and route map for the entire course
The cardinal ‘formula’ for a data scientist; The outcomes relating to Null Hypothesis and Alternate Hypothesis
Null Hypothesis statement and Alternate hypothesis statement; formulating them with some examples
The difference between one tail and two tail in a distribution curve; The four main types of tests and the testing flowpath. Performing the sample t - test using a case study
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;
Certified Six Sigma Master Black Belt
Project Management Professional (PMP)
Agile Certified Practitioner (PMI - ACP)
Risk Management Professional (PMI-RMP)
Certified Scrum Master
Agile Project Management – Foundation & Practitioner from APMG
Bharani Kumar is an Alumnus of premier institutions like IIT & ISB with 15+ years professional experience and worked in various MNCs such as HSBC, ITC, Infosys, Deloitte in various capacities such as Data Scientist, Project Manager, Service Delivery Manager, Process Consultant, Delivery Head etc.
He has trained over 1500 professionals across the globe on Business Analytics, Agile, PMP, Lean Six Sigma, Business analytics and the likes.
He has 8 years of extensive experience in corporate, open house and online training.
He is a thorough implementer with abilities in Business Analytics and Agile projects.
He worked in Delivery management focusing on maximizing business value articulation.
He has a comprehensive experience in leading teams and multiple projects.
Quality Management: A thorough implementer with abilities in Quality management focusing on maximizing customer satisfaction, process compliance and business value articulation; comprehensive experience in leading teams & multiple projects. A result-oriented leader with expertise in devising strategies aimed at enhancing overall organizational growth, sustained profitability of operations and improved business performance.
Project Management: Project Management Professional involved in Initiation, Planning, Execution, Monitoring & Controlling and Closing phases of project activities. Devising and implementing project plans within preset budgets and deadlines and managing the projects towards successful delivery of project deliverables and meeting project objectives.
Training: Close to 8 years training experience and conducted multiple trainings in PMP, Agile, Six Sigma, Business Analytics and Process Excellence across the globe. Understands the individual differences of the attendees and possesses excellent training skills and considered as one of the best trainers in his areas of expertise.