HippoCampus
MathematicsGuidedBeginner15 chapters

Statistics for reading the news without being fooled

HippoCampus
· starter course
I want to read news and studies without being misled: averages versus medians, sampling, margins of error, correlation versus causation, relative versus absolute risk, and misleading charts.

What you'll learn

15 chapters
  1. 1

    Why Statistics in the News Can Mislead

    • Recognize why statistical claims often appear in news coverage.
    • Identify common ways headlines oversimplify numbers.
    • Adopt a basic checklist mindset before trusting a numerical claim.
  2. 2

    Counts, Rates, Percentages, and Baselines

    • Tell apart raw counts, rates, and percentages.
    • Understand why baseline size matters when comparing groups.
    • Read common news numbers without confusing amount with proportion.
  3. 3

    Center: Mean, Median, and Typical Value

    • Define mean and median in plain language.
    • Choose which measure better describes a skewed set of values.
    • Interpret claims about what is 'typical' in a population.
  4. 4

    Spread, Range, and Outliers

    • Understand that a single average does not show how varied data are.
    • Use simple ideas of spread to interpret claims more carefully.
    • Recognize outliers and their effect on summaries.
  5. 5

    Percent Change and Time Trends

    • Read percentage increase and decrease claims correctly.
    • Interpret change over time with attention to starting values.
    • Avoid common mistakes when comparing trends across years.
  6. 6

    Where the Numbers Came From: Populations and Samples

    • Define population and sample.
    • Understand why most studies measure a subset rather than everyone.
    • See why sample quality matters as much as sample size.
  7. 7

    Sampling Bias and Who Was Left Out

    • Recognize major forms of sampling bias in news and survey reports.
    • Understand how exclusion can distort a result.
    • Ask practical questions about who was included and who was not.
  8. 8

    Polls, Uncertainty, and Margin of Error

    • Interpret a margin of error in simple terms.
    • Understand that poll results are estimates, not exact counts.
    • Read close poll results more cautiously.
  9. 9

    Studies in the News: Observational Research and Experiments

    • Distinguish observational studies from experiments.
    • Understand why study design affects what can be claimed.
    • Recognize why not all evidence supports the same kind of conclusion.
  10. 10

    Correlation Is Not Causation

    • Define correlation in plain language.
    • Explain why correlation alone does not prove one thing causes another.
    • Spot common causal overclaims in headlines.
  11. 11

    Confounding and Fair Comparisons

    • Understand confounding as a practical problem in comparisons.
    • Recognize why groups can differ in more than the headline variable.
    • Read study comparisons with more care.
  12. 12

    Relative Risk, Absolute Risk, and Big-Sounding Claims

    • Distinguish relative risk from absolute risk.
    • Interpret dramatic risk reductions in practical terms.
    • Avoid being misled by percentage framing alone.
  13. 13

    Statistical Significance, Practical Importance, and Uncertainty Language

    • Recognize that 'statistically significant' does not mean 'large' or 'important.'
    • Understand the difference between evidence of an effect and size of an effect.
    • Read uncertainty language in a more grounded way.
  14. 14

    Misleading Charts and Visual Tricks

    • Spot common chart choices that exaggerate or hide patterns.
    • Read axes, labels, and scales before trusting a visual impression.
    • Use basic visual skepticism when charts appear in news and social media.
  15. 15

    Putting It All Together: A Simple Checklist for News and Study Claims

    • Combine the course ideas into a practical reading routine.
    • Evaluate a statistical claim using source, measurement, comparison, uncertainty, and presentation.
    • Build confidence in asking better follow-up questions instead of accepting or rejecting claims too quickly.

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