13 modules · ~65 min
Data Literacy for Everyone
Understand, question, and talk about data with confidence — averages, percentages, charts, correlation, surveys, and A/B tests, in plain English for people who don't work in analytics.
This course is free — no account needed. Dive in.
What you'll be able to do
Explain what data literacy means — and why it isn't just for analysts
Know where business data comes from, and why the source decides whether you can trust it
Tell a metric from a measure, a target, and a KPI — and catch a vanity metric
Choose between average and median, and spot when the average is hiding the story
Read percentages with the right baseline, and separate percentage change from percentage points
Spot misleading charts: truncated axes, cherry-picked windows, and dual axes
Explain why correlation isn't causation — confounders, reverse causation, and survivorship
Judge surveys by who was asked and who answered, not just the headline number
Understand A/B tests and "statistical significance" — and why significant isn't the same as important
Ask the questions that separate a trustworthy number from a dressed-up one
Modules
13 in this track- 1What Data Literacy Actually Means (and Why It's Not Just for Analysts)FreeData literacy is the ability to understand, question, and communicate with data — and a dashboard is not automatically the truth. Where numbers go wrong on the way to a decision.Start →
- 2Where Data Comes From — and Why the Source Decides EverythingFreeOperational systems, surveys, spreadsheets, sensors, and manual entry — where business data is born, why two systems disagree about the same fact, and the difference between a source, a warehouse, and a dashboard.Start →
- 3Metrics, Measures, Targets & KPIs: Not Every Number Is a KPIFreeA measure, a metric, a target, and a key performance indicator are four different things — plus leading vs lagging indicators, and the vanity metric that looks great while the business stalls.Start →
- 4Averages vs Medians: The Number That Describes NobodyFreeMean, median, and why one big outlier can make "the average" a lie — plus the one follow-up question that protects you in any meeting.Start →
- 5Up 300% — From What? Percentages and BaselinesFreePercentage points vs percent, tiny baselines, cherry-picked comparisons, and the three-word question that deflates a misleading number: from what, exactly?Start →
- 6Reading Charts Without Being MisledFreeTruncated axes, convenient time windows, ever-rising cumulative curves, and dual axes — the four tricks behind most dramatic slides, and the three-second scan that defuses them.Start →
- 7Correlation vs Causation: Moving Together Isn't Caused ByFreeConfounders, reverse causation, and survivorship bias — the three boring explanations to rule out before believing X drives Y, and the experiment that settles it.Start →
- 8Surveys & Sample Sizes: Who Did They Ask?FreeWhy 500 random people beat a million volunteers, how response bias haunts every NPS score, and the questions that separate research from theater.Start →
- 9A/B Tests in Plain EnglishFreeSplit your users in two, change one thing, and compare — the experiment that finally earns the word "causes." Control vs treatment, random assignment, and why you decide what success means before you look.Start →
- 10"Is That Lift Significant?" — Statistical Significance in Plain EnglishFreeWhat people really mean by "statistically significant," why sample size decides whether a result is trustworthy, and why "not significant" doesn't mean "no effect." A coin-flip explanation, no formulas.Start →
- 11Significant Isn't the Same as ImportantFreeA result can be real and worthless, or shaky and worth chasing. Weighing strength of evidence, size of impact, scale, and cost — why 0.1% across millions beats 50% across three customers.Start →
- 12Before You Trust the Number: Asking Better QuestionsFreeThe whole course, distilled into the questions a data-literate person asks — worked through one real claim ("satisfaction up 30%!") that quietly breaks every rule, plus a checklist to keep.Start →
- 13Quick-Reference Glossary & Final CheckFreeEvery term from the course in one plain-English sentence with a workplace example — plus the final knowledge check that completes the course and earns your certificate.Start →