Test Of Hypothesis, Simplified Example-Based Approach

Friendly guide to formulate and test statistical hypothesis. Beginner-friendly approach is adopted with many examples.

What you'll learn
How to formulate a hypothesis
Understanding the test statistics
Utilizing confidence intervals and P-Values
Understanding of concerns about type I and type II errors
Make usage of Minitab software to check hypotheses
Use Matlab coding to check for hypotheses

Requirements
Curiosity and passion to learn should be sufficient
Pre-knowledge in elementary probabilities, statistics, and the normal distribution will be helpful

Description
In this course, students will be introduced to main aspects of statistical hypotheses. A simple approach is adopted to be beginners-friendly with several practical of examples to explain ideas. The course explains and develop skills toward proper hypotheses formulation and testing methodologies. Main points about hypotheses on the mean and variance of a population are covered.Students will learn how to correctly formulate a statistical hypothesis. They will also learn, in step by step, how to perform the right test for various types of hypotheses around the mean or the variance of a population. Interestingly, we will learn different methods to carry out correct hypothesis testing such as: test statistic, using confidence intervals and P-value.The course content is simplified to fit for beginners with minimal background in statistics. Also, it is highly focus on examples and less on complex theories. Certainly, a focus on practice with real world problems will also articulate the feel sense of the value of this knowledge.Finally, we make the use of both Minitab and Matlab software to help us quickly perform our tests. Friendly tutorials are given with examples for both software. Both software are introduced from absolute zero level, then students are guided with examples on how to use them for general purpose and specifically for working out tests of hypotheses.

Overview
Section 1: Introduction to Hypotheses Testing

Lecture 1 Refreshing about probabilities

Lecture 2 What is a hypothesis?

Lecture 3 Formulation of hypotheses

Lecture 4 Sampling distribution

Lecture 5 Quiz set 1

Section 2: Tests on Population Mean, Population Variance is Known

Lecture 6 Performing the test on the mean

Lecture 7 Confidence intervals

Lecture 8 P-Value

Lecture 9 Quick summary

Lecture 10 One sided tests

Lecture 11 More on one sided tests

Lecture 12 Summary

Lecture 13 Quiz set 2

Section 3: Tests on Population Mean, Population Variance is Unknown

Lecture 14 Performing the test

Lecture 15 Using confidence interval and P-Value

Lecture 16 Example: large sample size

Lecture 17 Quiz set 3

Section 4: Errors in Hypotheses Testing

Lecture 18 Type I and type II errors

Lecture 19 Choosing the sample size

Lecture 20 Quiz set 4

Section 5: Tests on Population Variance

Lecture 21 Performing the test

Lecture 22 One sided tests on the variance

Lecture 23 Confidence interval and P-Value

Lecture 24 Quiz set 5

Section 6: Minitab Software Tutorial

Lecture 25 Introduction to Minitab

Lecture 26 Performing the Z-tet

Lecture 27 Performing the t-test

Lecture 28 Tests on variance

Lecture 29 Quiz set 6

Section 7: Using Matlab for Hypothesis Testing

Lecture 30 Introduction to Matlab 1

Lecture 31 Introduction to Matlab 2

Lecture 32 Using M-Files in Matlab

Lecture 33 One sample Z test using Matlab

Lecture 34 Confidence Interval in Matlab for Z test

Lecture 35 P-Value in Matlab for Z test

Lecture 36 Matlab code files

Lecture 37 Performing t and chi^2 tests in Matlab

Lecture 38 Example: One sided test on variance using Matlab

Section 8: Appendices

Lecture 39 Appendix A: course material in PDF

Lecture 40 Main probability distributions tables (Ref: Montgomery and Runger)

Lecture 41 Operating Characteristic Curves (OCC) (Ref: Montgomery and Runger)

Students interested in statistics and statistical testing,Engineers doing experiments related to statistical measures,People working on data analysis and data interpretations

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