Hypothesis Testing : Essential Statistics For Data Science

A comprehensive study

What you'll learn

What is Hypothesis Testing? How to Frame Null & Alternative Hypothesis statements? What are the results of a hypothesis testing? And real-time examples.

Why do errors occur in hypothesis testing? What are Type I and Type II errors? How to choose Type I error ? How to balance between Type I & Type II errors?

How to use a point estimate to judge between Null & Alternative hypothesis? How to deploy Z or t statistic / table, calculate P-value, choose alpha and decide

What is Beta & Power of the hypothesis test? What factors influence Beta and Power of the test? How to estimate beta and power of the test?

Requirements

It is good for the student to have a little understanding on sample distributions, point estimate, Z / t test statistic and tables

Description

Hypothesis testing is one of the most essential topics in any statistical study and machine learning algorithmsP-value, alpha and point estimates find their foot prints in most of the statistical and ML studies.Hence it is important to understand hypothesis testing in as much detail as possible . The course includes five lecturesStarting the first lecture with the concepts that help you understand Hypothesis testing and what Null & Alternative hypothesis are. How to frame Null & Alternative hypothesis. Explain with a few real time examplesLecture 2 introduces you to the possible errors namely type I and Type II errors that occurs as a result of the hypothesis testing. Explains how to choose Type I error and balance between Type & II errorsThe third lecture is the main lecture and an elaborate one. Helps you understand how to apply the concepts and carry out the hypothesis testing applying all the essential statistical concepts. Explains all the statistical steps and their sequence involved in carrying out the hypothesis test until the conclusion is arrivedThe fourth lecture is dedicated for illustration of the hypothesis testing using real time examplesThe fifth and the final lecture explains you all about the power of the hypothesis test. The roll of type II error and it probability beta on the power of the testAll the above steps Comprehensively cover all the details in great level of granularity that at the end of the course I am sure you  will have a complete and a comprehensive understanding on Hypothesis testing and how to carry them out

Overview

Section 1: Introduction to Null and Alternative Hypotheses

Lecture 1 Introduction to Null & Alternative Hypothesis

Section 2: Type I & Type II errors

Lecture 2 Type I Type II errors

Section 3: Applying the concepts

Lecture 3 Applying the concepts

Section 4: Illustration with examples

Lecture 4 Illustration with examples

Section 5: Power of the Hypothesis Test and Beta

Lecture 5 Power of the Hypothesis test and Bets

Useful for Data science aspirants, and professionals across various disciplines involving management, medical, engineering and wide spectrum of disciplines