Mathew K AnalyticsStatistics for data analysts
A free 15-lesson course. Every lesson has a video walkthrough and a Jupyter notebook you can download or open in Google Colab; 14 lessons include real datasets. Tools covered: NumPy, pandas, SciPy, Matplotlib, statsmodels, itertools.
17 minLesson 1
Probability Foundations for Data Analysts | Statistics #1
16 minLesson 2
Discrete Distributions Explained: Binomial & Poisson | Statistics #2
18 minLesson 3
Continuous Distributions & the Normal Curve | Statistics #3
14 minLesson 4
The Central Limit Theorem, Finally Explained | Statistics #4
16 minLesson 5
Sampling Methods & How Bias Sneaks In | Statistics #5
16 minLesson 6
Confidence Intervals Done Properly | Statistics #6
16 minLesson 7
Hypothesis Testing Fundamentals | Statistics #7
16 minLesson 8
A/B Testing & Experiment Design That Works | Statistics #8
12 minLesson 9
Non-Parametric Tests: When Assumptions Fail | Statistics #9
13 minLesson 10
Multiple Comparisons & P-Value Corrections | Statistics #10
13 minLesson 11
Simple Linear Regression Explained | Statistics #11
13 minLesson 12
Multiple Regression & Model Diagnostics | Statistics #12
15 minLesson 13
Categorical Data Analysis & Chi-Square Tests | Statistics #13
15 minLesson 14
Bayesian Statistics Basics for Analysts | Statistics #14
15 minLesson 15