The Simplest & Easiest Course on Hypothesis Testing

Welcome to my complete course: the Introduction to Hypothesis Testing. This course is aimed for complete beginners or those struggling with introductory statistics.

I teach by breaking down complex concepts into little bite sized pieces and telling funny stories that stick! Good luck! :)

Check out this simple and intuitive example of Hypothesis Testing: Taking your mum bowling for her birthday. This lecture will ensure you clearly understand why we conduct this tests and that they are used commonly in everyday life, like seeing whether your best friend is lying to you!

This lecture shows how you already intuitively understand the basics of Hypothesis Testing, and that the remainder of this course is for you to learn these concepts formally and understand the statistical jargon. After this lecture, the hard part is already done :)

In this lecture, you will learn:

• Why Hypothesis Testing is required in practice
• How to refute a claim
• The intuition for rejection regions
• The intuition for significance levels
• The concept of Type 1 errors

Super simple and clear explanation of the differences between the population and a sample. Never get confused again!

In this lecture, you will learn:

• The distinction between the population and a sample
• The need for random sampling in Statistics

How to correctly set up your null and alternate hypothesis. Use this one simple rule and never this this step wrong!

In this lecture, you will learn:

• A fool-proof method (and simple rule) to setting up the null and alternate hypotheses

• How to formally write down the hypotheses in statistics

A discussion on the burden of proof in Hypothesis Testing.

In this lecture, you will learn:

• Why the null hypothesis is assumed true until proven otherwise

The 3 types of Hypothesis Tests you will encounter: Upper-, Lower-, and Two-Tailed Tests. Its very easy to identify them!

In this lecture, you will learn:

• All 3 types of Hypothesis Tests
• How they differ from each other
• How to identify each test in an exam setting

How to correctly set up the rejection region of your test. This is a simple yet crucial concept in Hypothesis Testing!

In this lecture, you will learn:

• The Normal distribution
• The setting up of the rejection regions in different types of Hypothesis Tests
• A simple rule to always correctly set up the rejection regions of your test

Let Judge Judy teach us about Type 1 errors and significance levels.

In this lecture, you will learn:

• Type 1 errors and why they are present in Hypothesis Testing
• Significance levels and how they are determined

Calculating Type 2 errors are often excluded from Introductory Statistics courses, so be sure to check your course outline.

In this lecture, you will learn:

• The definition of a Type 2 error

• Jump to the bonus lecture at the end of this course to learn how to calculate the probability of a Type 1 error!

Beginning our first worked example: a Lower-tailed Hypothesis Test. Let's go through this step-by-step in little chunks...

In this lecture, you will learn:

• How to conduct a lower-tailed Hypothesis Test
• How to work through the steps in the Hypothesis Testing framework

Introduction to the standard normal distribution (z-distribution) and why it is used in Statistics, and the concept of culmulative probabilities.

In this lecture, you will learn:

• Why standard normal distribution tables are needed in practice
• The characteristics of the standard normal distribution
• Cumulative probabilities of the standard nromal distribution

Learn how to use the Cumulative Standard Normal Probability Table, otherwise known as the Z-Table. It's easy to use, and it the most common table provided in Statistics textbooks. I'll also cover the 2 most important rules to using the Z-Table!

In this lecture, you will learn:

• How to use the Z-Table to calculate probabilities and z critical values
• Simple rules that makes the Z-Table versatile and easy to use

How to use another form of the Z-Table you may encounter.

In this lecture, you will learn:

• How to use alternative Z-Tables using the simple rules of the previous lecture

In this lecture, you will learn:

• How to use the Z-Table to find the z-critical value

Super easy explanation of standard errors and why they're so important in Hypothesis Testing.

In this lecture, you will learn:

• The concepts of testing mean values
• The definition of standard errors
• The nature of random sampling and why standard errors are needed

Calculating the critical value of the test!

In this lecture, you will learn:

• How to calculate the critical value of a Hypothesis Test
• How to interpret the critical value
• Why a critical value is needed in Hypothesis Testing

How to correctly conclude the test. The language here is very important, so be careful!

In this lecture, you will learn:

• The easiest method of concluding a Hypothesis Test
• The correct language to use when concluding the test

A complete summary of the steps for conducting a Hypothesis Test for a population mean.

In this lecture, you will learn:

• A useful summary of steps to complete the Hypothesis Testing process
• Tie together the application of the concepts covered in this section

A complete worked example of an Upper-Tailed Test. Are house prices too high? How would a Hypothesis Test be conducted in this scenario?

In this lecture, you will learn:

• How to complete an upper-tailed Hypothesis Test using the process outlined in Lecture 18

A complete worked example of a Two-Tailed Test. How old is the average age of Youtube viewers? Can we test this using Hypothesis Testing? Well, yes...yes we can...

In this lecture, you will learn:

• How to complete a two-tailed Hypothesis Test using the process outlined in Lecture 18

A summary of this section and what is to come in the next section. Congrats! You can now answer a Hypothesis Testing question, though there is more material to cover.