🕹️ Practice arcade
Extra games, not extra homework — timed sprints, survival runs that end when your lives run out, and mastery drills built from the same skills Statistics teaches.
⚡ Sprints
Beat the clock.
📊 Center & Spread Sprint
Median, variance, and standard deviation from a raw dataset -- sort it, deviate from the mean, and square, every time.
📏 Z-Score & Standard Error Sprint
Standardize a value against a mean and standard deviation, or shrink sigma by root n -- two different denominators, same idea of scale.
🎯 Margin of Error Sprint
z*-times-standard-error, three ways -- a plain margin, a full confidence-interval bound, and a proportion's own square-root formula.
🔬 Test Statistic & P-Value Sprint
Compute a z test statistic, convert it to a two-tailed p-value, or count degrees of freedom -- the arithmetic every hypothesis test runs on.
🔲 Chi-Square Sprint
Find an expected count under independence, then sum (O-E)^2/E across a table's cells.
📈 Correlation & ANOVA Sprint
Pearson's r from sums of squares, or an F statistic from two mean squares -- two different chapters' own single-formula payoffs.
🎯 Sampling Design Sprint
A systematic sample's own step size, or a stratum's proportional share of the total sample -- two chapter-2 sampling-design staples.
📊 Data Display Sprint
A reasonable class width from a data range, or a class's own relative frequency -- the arithmetic every frequency table and histogram runs on.
📐 Proportion Estimator Sprint
A sample proportion from a raw count, or a full confidence-interval bound built from it -- two chapter-11 staples back to back.
🔬 Two-Sample Test Statistic Sprint
A two-group t statistic from a given standard error, or a pooled two-proportion z statistic built from scratch.
🤝 Paired & Difference Interval Sprint
A paired t statistic from mean difference and its own spread, or a difference interval's margin of error from a given standard error.
🔲 Chi-Square Degrees-of-Freedom Sprint
Independence's (r-1)(c-1), or goodness-of-fit's k-1 -- the same n-1 mistake tempts both, and this sprint drills telling them apart.
📈 Regression Prediction & Residual Sprint
Read a fitted value straight off a least-squares line, or find one point's own leftover miss.
📉 R-Squared & Standard Error Sprint
The proportion of variance a line explains, or the typical size of a residual in the data's own units -- two different readings of the same leftover spread.
🧮 Adjusted R-Squared & ANOVA Identity Sprint
Rescale R^2 for an added predictor, or complete the SST=SSB+SSW split -- two chapters' own variance-accounting identities.
🔀 Nonparametric Rank Sprint
Count signs, sum signed ranks into W, or turn pooled ranks into U -- all three of this course's rank-based tests, back to back.
💀 Survival
Each miss costs a life — lose them all and the run ends.
🎯 Mastery
No clock — just get N in a row.
🤝 Pooling & Effect Size Mastery
Pool two samples' variances, then turn a mean difference into Cohen's d -- five clean two-group computations in a row, no clock.
📦 Five-Number Summary Mastery
Find Q1 or Q3 as the median of the correct half, excluding the overall median -- five clean reads in a row, no clock.