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Beginner · free

Practical Statistics for Everyday Decisions

Turn spreadsheets of orders, surveys, and tickets into confident, data-backed decisions.

For analysts, marketers, and managers who work in Excel and want to make decisions from data with confidence..

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Describing and Understanding Data Watch this part on YouTube

Start here

1 lesson
  1. Welcome to the course: what you will learn Welcome 5 min

Module 1: Data Foundations with Pandas

6 lessons
  1. Track overview: Describing and Understanding Data Introduction 5 min
  2. Why statistics matters for everyday decisions: from gut feel to numbers Lesson 1 8 min
  3. Loading and inspecting data: pandas DataFrames for order and survey data Lesson 2 9 min
  4. Cleaning messy data: missing values, duplicates, and data types Lesson 3 10 min
  5. Grouping and summarizing: pandas groupby for quick business answers Lesson 4 11 min
  6. Project: build a clean orders dataset and answer three business questions Lesson 5 11 min

Module 2: Describing Data: Center and Spread

5 lessons · coming soon
  1. Mean, median, and mode: which average tells the truth Lesson 1 coming soon
  2. Spread: range, variance, and standard deviation explained simply Lesson 2 coming soon
  3. Percentiles and quartiles: finding typical and extreme values Lesson 3 coming soon
  4. Box plots: spotting outliers and comparing groups at a glance Lesson 4 coming soon
  5. Project: describe support ticket resolution times and flag outliers Lesson 5 coming soon

Module 3: Visualizing Distributions

5 lessons · coming soon
  1. Histograms: seeing the shape of your data with matplotlib Lesson 1 coming soon
  2. Skewness and shape: symmetric, left-skewed, right-skewed data Lesson 2 coming soon
  3. Comparing distributions across groups: overlays and small multiples Lesson 3 coming soon
  4. Choosing the right chart: histogram vs box plot vs bar chart Lesson 4 coming soon
  5. Project: compare order values across customer segments visually Lesson 5 coming soon

Module 4: Probability and Distributions in Plain Words

5 lessons · coming soon
  1. Probability basics: chances, odds, and everyday misunderstandings Lesson 1 coming soon
  2. The normal distribution: the bell curve and the 68-95-99.7 rule Lesson 2 coming soon
  3. The binomial distribution: counting successes in repeated trials Lesson 3 coming soon
  4. Expected value: what it means and how to compute it in Python Lesson 4 coming soon
  5. Project: estimate expected revenue from a promotion using probability Lesson 5 coming soon

Testing Ideas and Finding Relationships Watch this part on YouTube

Module 5: Sampling and Uncertainty

6 lessons · coming soon
  1. Track overview: Testing Ideas and Finding Relationships Introduction coming soon
  2. Populations vs samples: why we can't survey everyone Lesson 1 coming soon
  3. Why samples vary: sampling error and the sampling distribution Lesson 2 coming soon
  4. The Central Limit Theorem in plain words, with a simulation Lesson 3 coming soon
  5. Confidence intervals: how sure are we about an estimate Lesson 4 coming soon
  6. Project: estimate average order value with a confidence interval Lesson 5 coming soon

Module 6: Hypothesis Testing Without Fear

5 lessons · coming soon
  1. What a hypothesis test actually does: null, alternative, and logic Lesson 1 coming soon
  2. P-values explained: what they do and don't mean Lesson 2 coming soon
  3. Common traps: p-hacking, multiple testing, and misreading significance Lesson 3 coming soon
  4. One-sample and two-sample t-tests in Python Lesson 4 coming soon
  5. Project: test whether a new checkout page changed average order value Lesson 5 coming soon

Module 7: A/B Testing in Practice

5 lessons · coming soon
  1. Designing a fair A/B test: randomization and sample size Lesson 1 coming soon
  2. Testing conversion rates: proportions and the chi-square test Lesson 2 coming soon
  3. Reading A/B test results: effect size, confidence, and business impact Lesson 3 coming soon
  4. When A/B tests mislead: peeking early, novelty effects, and seasonality Lesson 4 coming soon
  5. Project: analyze a website A/B test and recommend a decision Lesson 5 coming soon

Module 8: Relationships: Correlation and Regression

5 lessons · coming soon
  1. Correlation: measuring how two variables move together Lesson 1 coming soon
  2. Correlation is not causation: classic traps and how to spot them Lesson 2 coming soon
  3. Simple linear regression: fitting a line to explain a relationship Lesson 3 coming soon
  4. Interpreting regression output: slope, intercept, and R-squared Lesson 4 coming soon
  5. Project: predict support ticket volume from orders and decide staffing Lesson 5 coming soon