Crash Course Statistics: study plan and how long it takes
The CrashCourse playlist is 45 videos and 8.8 hours long. Here's how long it takes at different paces, a week-by-week schedule built from the real videos, and a planner that turns it into your own daily plan.
45 videos · 8.8 hours · CrashCourse
Crash Course Statistics, hosted by Adriene Hill, explains statistics through real-world examples: data visualization, sampling and bias, distributions, confidence intervals, Bayesian reasoning, p-hacking, model fitting, and statistics in courts and predictions.
Each episode is about 12 minutes, so it's an easy daily habit.
Who it's for: Beginners and non-specialists who want to understand statistics and spot bad statistics in the news.
How long does it take?
The full playlist is 8.8 hours across 45 videos. Here's roughly how many days that is at different daily watch times and speeds, counting video time only:
| Daily time | At 1x | At 1.5x | At 2x |
|---|---|---|---|
| 30 min a day | 18 days | 12 days | 9 days |
| 1 h a day | 9 days | 6 days | 5 days |
| 2 h a day | 5 days | 3 days | 3 days |
Make your own schedule
The playlist link is already filled in. Press Plan, set how much time you have each day and your speed, and you'll get a day-by-day schedule with a finish date and a calendar file. It reads the live playlist, so new videos are included.
Week-by-week schedule
A sample plan at 1 hour a day and normal speed, using whole videos so none is split across days. That's 2 weeks in total. For a different pace, start date or speed, use the planner above.
Week 1Videos 1–32 · 6h 12m
Day 1 · 50m
- 1Crash Course Statistics Preview3m
- 2What Is Statistics: Crash Course Statistics #113m
- 3Mathematical Thinking: Crash Course Statistics #211m
- 4Mean, Median, and Mode: Measures of Central Tendency: Crash Course Statistics #311m
- 5Measures of Spread: Crash Course Statistics #412m
Day 2 · 58m
- 6Charts Are Like Pasta - Data Visualization Part 1: Crash Course Statistics #510m
- 7Plots, Outliers, and Justin Timberlake: Data Visualization Part 2: Crash Course Statistics #612m
- 8The Shape of Data: Distributions: Crash Course Statistics #711m
- 9Correlation Doesn't Equal Causation: Crash Course Statistics #812m
- 10Controlled Experiments: Crash Course Statistics #912m
Day 3 · 58m
- 11Sampling Methods and Bias with Surveys: Crash Course Statistics #1012m
- 12Science Journalism: Crash Course Statistics #1111m
- 13Henrietta Lacks, the Tuskegee Experiment, and Ethical Data Collection: Crash Course Statistics #1211m
- 14Probability Part 1: Rules and Patterns: Crash Course Statistics #1312m
- 15Probability Part 2: Updating Your Beliefs with Bayes: Crash Course Statistics #1412m
Day 4 · 59m
- 16The Binomial Distribution: Crash Course Statistics #1514m
- 17Geometric Distributions and The Birthday Paradox: Crash Course Statistics #1610m
- 18Randomness: Crash Course Statistics #1712m
- 19Z-Scores and Percentiles: Crash Course Statistics #1811m
- 20The Normal Distribution: Crash Course Statistics #1911m
Day 5 · 49m
- 21Confidence Intervals: Crash Course Statistics #2013m
- 22How P-Values Help Us Test Hypotheses: Crash Course Statistics #2112m
- 23P-Value Problems: Crash Course Statistics #2212m
- 24Playing with Power: P-Values Pt 3: Crash Course Statistics #2312m
Day 6 · 47m
- 25You Know I'm All About that Bayes: Crash Course Statistics #2412m
- 26Bayes in Science and Everyday Life: Crash Course Statistics #2511m
- 27Test Statistics: Crash Course Statistics #2613m
- 28T-Tests: A Matched Pair Made in Heaven: Crash Course Statistics #2711m
Day 7 · 50m
- 29Degrees of Freedom and Effect Sizes: Crash Course Statistics #2814m
- 30Chi-Square Tests: Crash Course Statistics #2911m
- 31P-Hacking: Crash Course Statistics #3011m
- 32The Replication Crisis: Crash Course Statistics #3115m
Week 2Videos 33–45 · 2h 34m
Day 8 · 50m
- 33Regression: Crash Course Statistics #3213m
- 34ANOVA: Crash Course Statistics #3313m
- 35ANOVA Part 2: Dealing with Intersectional Groups: Crash Course Statistics #3413m
- 36Fitting Models Is like Tetris: Crash Course Statistics #3511m
Day 9 · 58m
- 37Supervised Machine Learning: Crash Course Statistics #3612m
- 38Unsupervised Machine Learning: Crash Course Statistics #3711m
- 39Intro to Big Data: Crash Course Statistics #3811m
- 40Big Data Problems: Crash Course Statistics #3913m
- 41Statistics in the Courts: Crash Course Statistics #4011m
Day 10 · 45m
- 42Neural Networks: Crash Course Statistics #4112m
- 43War: Crash Course Statistics #4211m
- 44When Predictions Fail: Crash Course Statistics #4311m
- 45When Predictions Succeed: Crash Course Statistics #4411m
Tips for finishing
- Two episodes a day gets you through in about three weeks.
- Follow it with StatQuest's Statistics Fundamentals for more depth on each idea.