Study guide
Statistics for Everyday Life study guide
Statistics is one of the most misunderstood subjects, because it is usually taught as a collection of formulas rather than as a way of understanding uncertainty.
- Modules
- 7 modules
- Lessons
- 48 lessons
- Estimated time
- ~12-16 hours
- Key terms
- 92 key terms
How to work through it
- 1. Follow the order below. The modules build on each other — start at the top and work down.
- 2. Recall before you re-read. After each lesson, try to explain the idea from memory, then check yourself with the flashcards.
- 3. Test at the end of each module. The quizzes below show what stuck and what to review.
Full lesson outline
Module 1. Understanding Data
Module 2. Making Sense of Evidence
Module 3. Probability and Prediction
Module 4. Working with Data
Module 5. Statistics in Society
Module 6. The Ideas of Statistics
Module 7. The Statistician's Toolkit
Practise & review
- Glossary92 terms defined in plain language
- FlashcardsDrill the vocabulary with active recall
- Understanding Data quiz12 questions, graded instantly
- Making Sense of Evidence quiz13 questions, graded instantly
- Probability and Prediction quiz14 questions, graded instantly
- Working with Data quiz14 questions, graded instantly
- Statistics in Society quiz14 questions, graded instantly
- The Ideas of Statistics quiz14 questions, graded instantly
- The Statistician's Toolkit quiz14 questions, graded instantly
- Percentage calculatorFree statistics tool
- Mean, median & mode calculatorFree statistics tool
- Standard deviation calculatorFree statistics tool
- Z-score calculatorFree statistics tool
- Weighted average calculatorFree statistics tool
- Confidence interval calculatorFree statistics tool
- Sample size calculatorFree statistics tool
Key terms
The vocabulary you’ll meet, each linked to its full definition in the glossary.
- A/B test
- Absolute risk
- ANOVA
- Base rate
- Base-rate fallacy
- Bayes’ theorem
- Bayesian statistics
- Bin width
- Box plot
- Calibration
- Categorical data
- Cherry-picking
- Chi-square test
- Conditional probability
- Confidence interval
- Confounder
- Conjunction fallacy
- Consumer price index
- Contingency table
- Continuous data
- Correlation coefficient
- Data analysis workflow
- Data cleaning
- Data literacy
- Descriptive statistics
- Discrete data
- Distribution
- Effect size
- Expected value
- Exploratory data analysis
- Extrapolation
- Forecast
- Frequentist statistics
- Gambler's fallacy
- Gambler’s fallacy
- Histogram
- Independence
- Independent events
- Inferential statistics
- Interquartile range
- Margin of error
- Mean
- Median
- Missing data
- Mode
- Multiple comparisons
- Multiple regression
- Multiple-comparisons problem
- Natural experiment
- Natural variation
- Non-response bias
- Nonparametric methods
- Number needed to treat
- Numerical data
- Ordinal data
- Outlier
- Overfitting
- p-hacking
- p-value
- Percentage point
- Population
- Probability
- Publication bias
- R-squared
- Random sampling
- Randomized controlled trial
- Randomness
- Range
- Regression
- Regression to the mean
- Relative risk
- Replication
- Risk difference
- Risk of ruin
- Robust statistics
- Sabermetrics
- Sample
- Scatter plot
- Selection bias
- Sensitivity
- Simpson’s paradox
- Skew
- Specificity
- Spurious correlation
- Standard deviation
- Statistical power
- Statistical significance
- Statistics
- Survivorship bias
- t-test
- Training and test data
- Variance