The Simplest & Easiest Course on Hypothesis Testing

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

Just a quick quiz to re-cap some of the concepts covered so far.

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!

Just a quick quiz to re-cap some of the concepts covered so far.

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.

Welcome to Section 2 of the course! Its time to learn a few more concepts to polish up your knowledge. But not to worry, its only a minor extension of what you already know!

A quick overview of the 3 methods to answering a Hypothesis Testing question for one population mean. We've already covered the Critical Value method in Section 1 of this course. Only 2 more to go!

In this lecture, you will learn:

• That there are 3 methods of answering a Hypothesis Testing question
• All 3 methods provide you with the same conclusion

A quick review of the Critical Value method as taught in Section 1.

In this lecture, you will cover:

• A quick refresher of the Critical Value Method which was taught in Section 1

This is a complete lecture on the Z-Score method. I teach this method in a step-by-step manner and slowly work through an example from Section 1.

In this lecture, you will learn:

• The Z-Score Method of completing a Hypothesis Testing question
• The difference between the Z-Score and Critical Value methods
• A summary of steps for the Z-Score method

Introduction to the P-Value, and an overview of how it is used in Hypothesis Testing. This is one of the most important concepts in Statistics. Don't worry, I've broken it down into little bite sized digestible pieces :)

In this lecture, you will learn:

• What the p-value is
• The interpretation of the p-value
• How to use the p-value to easily answer Hypothesis Testing questions

A detailed step-by-step worked example to demonstrate how to implement the P-Value method of Hypothesis Testing.

In this lecture, you will learn:

• How to calculate the p-value for solving a Hypothesis Test
• A useful summary of steps to complete the Hypothesis Test using the P-Value method.

This is a quick quiz to re-cap some of the concepts covered so far.

In reality, we cannot observe the population standard deviation. If this is the case, then how do we proceed? This short lecture will tell us how. Its easy!

In this lecture, you will learn:

• How to complete a Hypothesis Test when the population standard deviation is unknown

A quick introduction to the Student T Distribution. This is used in place of the Standard Normal Distribution when you only have the sample standard deviation to work with.

In this lecture, you will learn:

• About the Student T Distribution
• How it differs from the Z-Distribution

A complete step-by-step solution for a Hypothesis Testing question when only the sample standard deviation is available, hence, students must use the Student T distribution.

In this lecture, you will learn:

• How to complete a Hypothesis Testing question using the sample standard deviation
• How to apply the Student T Distribution in a Hypothesis Test
• A useful summary of steps that clarifies the process of using a sample standard deviation in a Hypothesis Test

There's an extra step for calculating the p-value for a 2-tailed test, and since students find the p-value method the most difficult, here is another complete worked example!

In this lecture, you will learn:

• How to apply the P-Value method to a two-tailed Hypothesis Test using a simple rule

An introduction to the Central Limit Theorem and how it relates to Hypothesis Testing. Sometimes it can be impossible to answer a Hypothesis Testing question...

In this lecture, you will learn:

• The general properties of the Central Limit Theorem (CLT)
• How the CLT affects Hypothesis Tests

This lecture covers how we conduct a Hypothesis Test on proportions. For example, more than half of Udemy students are females. How can we test this claim?

This is a minor extension of what we've covered so far, and is a piece of cake!

In this lecture, you will learn:

• How to complete a Hypothesis Test for proportions
• How it differs from a Hypothesis Test using a continuous variable (as in all previous lectures)
• A summary of steps to completing a Hypothesis Test with proportions question

A quick quiz to re-cap some of the concepts covered so far.

Summary of this Section and some important reminders of the concepts covered. Congrats! You've now finished the guts of this Course :)

It is suggested that you attempt the questions without referring to the solutions initially. If you get stuck, then refer to the solutions and complete the question. The next day, attempt the question again without referring to the solutions.

Use the answers in this Lecture to check your work. GOOD LUCK!

This is a step-by-step worked example on how to answer a Hypothesis Testing question on the Type 2 error of a test. This procedure is sometimes omitted from Introductory Statistics courses, so be sure to check your course outline to see if it is included.

In this lecture, you will learn:

• How to calculate the probability of a Type 2 error and apply it to an exam-style question
• The difference between the distribution of the test and the true distribution of sample means