Professor Leonard's Statistics: study plan and how long it takes
The Professor Leonard playlist is 28 videos and 31.9 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.
28 videos · 31.9 hours · Professor Leonard
Professor Leonard's statistics course is a full-length college course recorded in his classroom: key definitions and sampling, describing data, measures of centre and spread, z-scores and percentiles, probability rules, probability distributions, the normal distribution and central limit theorem, confidence intervals and hypothesis testing.
Lectures are long, often over an hour, and his patient explanations are famous among students.
Who it's for: College students taking an introductory statistics course who want every step explained.
How long does it take?
The full playlist is 31.9 hours across 28 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 | 64 days | 43 days | 32 days |
| 1 h a day | 32 days | 22 days | 16 days |
| 2 h a day | 16 days | 11 days | 8 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 4 weeks in total. For a different pace, start date or speed, use the planner above.
Week 1Videos 1–8 · 8h 50m
Day 1 · 49m
- 1Statistics Lecture 1.1: The Key Words and Definitions For Elementary Statistics17m
- 2Statistics Lecture 1.3: Exploring Categories of Data, Levels of Measurement32m
Day 2 · 32m
- 3Statistics Lecture 1.5: Sampling Techniques. How to Develop a Random Sample32m
Day 3 · 1h 7m
- 4Statistics Lecture 2.2: Creating Frequency Distribution and Histograms1h 7m
Day 4 · 1h 11m
- 5Statistics Lecture 3.2: Finding the Center of a Data Set. Mean, Median, Mode1h 11m
Day 5 · 1h 56m
- 6Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set1h 56m
Day 6 · 1h 32m
- 7Statistics Lecture 3.4: Finding Z-Score, Percentiles and Quartiles, and Comparing Standard Deviation1h 32m
Day 7 · 1h 42m
- 8Statistics Lecture 4.2: Introduction to Probability1h 42m
Week 2Videos 9–15 · 7h 53m
Day 8 · 1h 10m
- 9Statistics Lecture 4.3: The Addition Rule for Probability1h 10m
Day 9 · 1h 6m
- 10Statistics Lecture 4.4: The Multiplication Rule for "And" Probabilities.1h 6m
Day 10 · 33m
- 11Statistics Lecture 4.5: Probability of Complementary Events with "At Least One"33m
Day 11 · 1h 37m
- 12Statistics Lecture 4.7: Fundamental Counting Rule, Permutations and Combinations1h 37m
Day 12 · 1h 13m
- 13Statistics Lecture 5.2: A Study of Probability Distributions, Mean, and Standard Deviation1h 13m
Day 13 · 1h 33m
- 14Statistics Lecture 5.3: A Study of Binomial Probability Distributions1h 33m
Day 14 · 42m
- 15Statistics Lecture 5.4: Finding Mean and Standard Deviation of a Binomial Probability Distribution42m
Week 3Videos 16–22 · 9h 44m
Day 15 · 2h 11m
- 16Statistics Lecture 6.2: Introduction to the Normal Distribution and Continuous Random Variables2h 11m
Day 16 · 57m
- 17Statistics Lecture 6.3: The Standard Normal Distribution. Using z-score, Standard Score57m
Day 17 · 50m
- 18Statistics Lecture 6.4: Sampling Distributions Statistics. Using Samples to Approx. Populations50m
Day 18 · 1h 31m
- 19Statistics Lecture 6.5: The Central Limit Theorem for Statistics. Using z-score, Standard Score1h 31m
Day 19 · 2h 24m
- 20Statistics Lecture 7.2: Finding Confidence Intervals for the Population Proportion2h 24m
Day 20 · 49m
- 21Statistics Lecture 7.3: Confidence Interval for the Sample Mean, Population Std Dev -- Known49m
Day 21 · 1h 1m
- 22Statistics Lecture 7.4: Confidence Interval for the Sample Mean, Population Std Dev -- Unknown1h 1m
Week 4Videos 23–28 · 5h 29m
Day 22 · 32m
- 23Statistics Lecture 7.5: Confidence Intervals for Variance and Std Dev. Chi-Squared Distribution.32m
Day 23 · 2h 27m
- 24Statistics Lecture 8.2: An Introduction to Hypothesis Testing2h 27m
Day 24 · 1h 10m
- 25Statistics Lecture 8.3: Hypothesis Testing for Population Proportion1h 10m
Day 25 · 27m
- 26Statistics Lecture 8.4: Hypothesis Testing for Population Mean. Population Std Dev is Known.27m
Day 26 · 53m
- 27Statistics Lecture 8.5: Hypothesis Testing for Population Mean. Population Std Dev is Unknown.38m
- 28Statistics Lecture 8.6: Hypothesis Testing Involving Variance and Standard Deviation.14m
Tips for finishing
- Work the examples along with him on paper; that's how his lectures are meant to be watched.
- Long lectures get their own day in the planner. Set a daily time you can really focus for.