Basic arithmetic and familiarity with tables and graphs are helpful. More advanced probability or inference topics assume the prerequisite methods shown in the recordings.
Optional preparation: Statistics Fundamentals: Free Course.
About this course
A significance test asks how compatible observed evidence is with a specified null model. This course develops hypotheses, test statistics, P-values, errors and statistical power. Study the complete public source playlist from Khan Academy in English, with all 22 recordings in the on-site classroom. Original lesson titles, source order and repeated entries are preserved.
Course at a glance
| Provider / Teaching team | Khan Academy |
|---|---|
| Platform | YouTube · Khan Academy |
| Access | Free Video |
| Level | Intermediate |
| Language | English |
| Videos | 22 |
| Video duration | 2h 3m · allow extra time for practice |
| Format | Self-paced recorded training |
| Certificate | Not included with video viewing |
What you’ll learn
- Write null and alternative hypotheses in context.
- Select and check a proportion or mean test.
- Interpret P-values and significance decisions.
- Explain Type I errors, Type II errors and power.
Skills you’ll gain
- Hypothesis tests
- P-values
- Statistical power
- Inference conditions
Course Overview
Proportion and mean examples show how to write null and alternative hypotheses before calculating a z or t statistic. Tables, calculators and simulations provide different ways to obtain or estimate a P-value. The conclusion lessons connect that value with a chosen significance level while retaining the question's direction and context. Type I and Type II errors describe different mistakes, and power considers the chance of detecting a specified departure from the null. Conditions are checked separately for proportion and mean procedures. Keep a P-value distinct from the probability that a hypothesis is true, and distinguish statistical evidence from the size or practical importance of an effect.
How to study the course
- Videos 1–5: this part of the source list includes “When to use z or t statistics in significance tests” through “Constructing hypotheses for a significance test about a proportion”. Define the question and the observations. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
- Videos 6–11: this part of the source list includes “Free response example: Significance test for a mean” through “Introduction to Type I and Type II errors”. Check the assumptions behind a method. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
- Videos 12–16: this part of the source list includes “Comparing P-value from t statistic to significance level” through “Calculating a P-value given a z statistic”. Connect a calculation with a plain-language interpretation. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
- Videos 17–22: this part of the source list includes “Making conclusions in a test about a proportion” through “Using a table to estimate P-value from t statistic”. Describe uncertainty and limits of a conclusion. Keep a brief working note, revisit an unclear explanation and test one example before moving to another part of the material.
Who is this for?
This course suits students, analysts and readers who want to understand the specific statistical methods in the course. It also provides a recorded reference for revisiting a topic after an earlier lesson or study attempt. Choose examples appropriate to your background and allow time to work through the method instead of judging understanding only by how familiar the terminology sounds.
Before you start
Basic arithmetic and familiarity with tables and graphs are helpful. More advanced probability or inference topics assume the prerequisite methods shown in the recordings.
Put the lessons into practice
Prepare a fictional one-sample testing question and state the parameter, hypotheses and significance level. Check the conditions, calculate the test statistic and interpret the P-value under the null model. Write the conclusion without claiming that a hypothesis has been proved. Describe both possible error types in the language of your example.
This optional study activity is provided by WikiFree for independent practice. Keep your working notes and use the relevant classroom recording to check a step, definition or interpretation. It is not an instructor-marked assignment.
Certificate / Assessment
Watching the public videos and using WikiFree completion tracking does not award a certificate, academic credit, an examination voucher or instructor assessment. Use your practice output to review what you can explain and repeat independently. The recorded lessons provide study material; completion tracking records your progress through that material.
Related courses for your next step
- Review a lower-level optionStatistics Fundamentals: Free Course
Focus: Descriptive statistics · Probability
Beginner - Review a lower-level optionStatistical Study Design: Free Course
Focus: Sampling · Survey bias
Beginner - Review a lower-level optionHigh School Statistics: Free Course
Focus: Descriptive statistics · Probability
Beginner - Compare another approachFree MIT Course: Applied Statistics and Statistical Inference
Focus: 1. Introduction to Statistics · 6. Maximum Likelihood Estimation (cont.) and the Method of Moments
Intermediate
Compare course focus, level and study time
| Course | Level | Focus | Study time |
|---|---|---|---|
| This course — Statistical Hypothesis Testing: Free Course | Intermediate | Hypothesis tests · P-values · Statistical power | 2h 3m of video; practice time is additional |
| Statistics Fundamentals: Free Course | Beginner | Descriptive statistics · Probability · Sampling | 2h 0m of video; practice time is additional |
| Statistical Study Design: Free Course | Beginner | Sampling · Survey bias · Experimental design | 1h 11m of video; practice time is additional |
| High School Statistics: Free Course | Beginner | Descriptive statistics · Probability · Study design | 6h 19m of video; practice time is additional |
| Free MIT Course: Applied Statistics and Statistical Inference | Intermediate | 1. Introduction to Statistics · 6. Maximum Likelihood Estimation (cont.) and the Method of Moments · 12. Testing Goodness of Fit (cont.) | 28h 0m of video; practice time is additional |
Frequently asked questions
Is this course free to watch?
Yes. The public source videos are available in the WikiFree classroom. Video viewing does not include separately priced tools, hardware, memberships or a credential.
How long does the course take?
The 22 source video occurrences total approximately 2h 3m. Allow additional time for pausing, notes, practice and revisiting an explanation.
What background do I need?
Basic arithmetic and familiarity with tables and graphs are helpful. More advanced probability or inference topics assume the prerequisite methods shown in the recordings.
Does completing the videos award a certificate?
No. Video viewing and WikiFree progress tracking do not award a certificate, academic credit or an exam voucher.
Can I study on a phone?
Yes. The classroom supports a responsive player and searchable lesson list. A larger screen or a suitable practice environment can help with detailed calculations, diagrams and software examples.
Provider: Khan Academy. Videos play from the Khan Academy channel on YouTube.
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