Statistics Quest

Statistical Thinking

What statistics is for, and how data are produced, before any formula.

Populations and samples, variables and measurement scales, observational studies and experiments, bias, confounding and uncertainty. You will learn to ask where numbers came from and what they can and cannot support.

Lessons

  1. 1What statistics is forExplain how statistics turns variable data into evidence for decisions, and tell descriptive from inferential questions.20 minFree
  2. 2Populations, samples, parameters and statisticsIdentify the population, sample, parameter and statistic in a study, use the standard notation, and compute a sample proportion.25 minFree
  3. 3Variables and observationsIdentify the unit of observation in a dataset and classify each variable as categorical or quantitative, discrete or continuous.20 minFree
  4. 4Measurement scalesClassify variables as nominal, ordinal, interval or ratio, and choose only the arithmetic and summaries each scale supports.25 minFree
  5. 5Observational studies and experimentsDistinguish observational studies from randomised experiments, identify explanatory and response variables, and explain why random assignment supports causal conclusions.30 minFree
  6. 6Where data come fromClassify data sources, distinguish random from systematic measurement error, and check a dataset's documentation and provenance before trusting it.25 minFree
  7. 7Bias and representative samplesRecognise selection, nonresponse, response and measurement bias, and explain why a larger biased sample does not fix bias.30 minFree
  8. 8Confounding and causationIdentify confounding variables, explain why association does not establish causation, and see how comparing like with like changes a conclusion.35 minFree
  9. 9Uncertainty and significanceExplain sampling variability, compute and interpret an approximate margin of error for a proportion, and distinguish statistical significance from practical importance.35 minFree
  10. 10Critiquing statistical claimsEvaluate a statistical claim systematically — source, sample, design, measure, comparison, effect size and uncertainty — and rewrite it honestly.35 minFree