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Statistics for Data Science

Free

Descriptive statistics, spread and variability, distributions, and skewness — building real statistical intuition through interactive visualizations.

4 modules · Free with a (free) account.

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What this course covers

A module-by-module concept outline. Open the course to learn each topic with animated explanations, in-browser code, practice challenges, and a knowledge check.

Module 1. Finding the Center

Topics

Why Do We Need This?The Mean (Average)The Median (Middle Value)The Mode (Most Popular)Which One Should You Use?

Sections

1Why Do We Need This?
2The Mean (Average)
3The Median (Middle Value)
4The Mode (Most Popular)
5Which One Should You Use?

Module 2. Measuring the Spread

Topics

Why Spread MattersRange and QuartilesVariance and Standard DeviationBox PlotsReal-World Examples

Sections

1Why Spread Matters
2Range and Quartiles
3Variance and Standard Deviation
4Box Plots
5Real-World Examples

Module 3. Understanding Distributions

Topics

The Normal DistributionThe 68-95-99.7 RuleZ-ScoresSkewnessOther Distribution Shapes

Sections

1The Normal Distribution
2The 68-95-99.7 Rule
3Z-Scores: Standardizing Data
4Skewness: When Data Isn't Symmetric
5Other Distribution Shapes

Module 4. Understanding Skewness

Topics

What is Skewness?Why Does Data Get Skewed?When to Use Median Instead of MeanSpotting Misleading StatisticsComparing Measures Across Distributions

Sections

1What is Skewness?
2Why Does Data Get Skewed?
3When to Use Median Instead of Mean
4Spotting Misleading Statistics
5Comparing Measures Across Distributions

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All course syllabi

SQL Fundamentals SQL Mastery SQL Window Functions Python Fundamentals Pandas Fundamentals Probability for Data Scientists Machine Learning Fundamentals (scikit-learn)A/B Testing & Experimentation LLM Foundations