Statistics Playground — learn statistics & machine learning interactively

An interactive playground for probability, statistics and machine learning — pick a concept, edit its parameters, and see the distribution curve, the computed value and a plain-English explanation, all computed in your browser. The functions mirror familiar R syntax (e.g. pnorm, dbinom, t.test) with the equivalent Python (numpy/scipy) alongside. Around the playground: timed practice exams, ten statistics games, a printable cheat sheet, statistical tables, a glossary, and free R and Python coding playgrounds — no account, no install.

Topics & functions

Visualizing data

• barplot — Bar chart
• pie — Pie chart
• donut — Donut chart
• stackedbar — Stacked bar chart
• hist — Histogram
• histtable — Histogram (from a table)
• cumfreq — Cumulative frequency
• boxplot — Box plot
• density — Density (KDE)
• violin — Violin plot
• qqplot — Q-Q plot
• plot — Line chart
• area — Area chart
• waterfall — Waterfall chart
• scatter — Scatter plot
• bubble — Bubble chart
• corrheatmap — Correlation heatmap

Central tendency

• mean — The average
• median — The middle value
• mode — The most common value
• compare — Mean vs median vs mode

Measuring spread

• range — Range (min to max)
• percentile — Percentiles
• IQR — Interquartile range
• var — Variance
• sd — Standard deviation
• zscore — Z-scores

Probability

• probrules — Probability rules
• condprob — Conditional probability
• sample — Random sampling
• bayes — Bayes’ theorem

Expectation

• weighted.mean — Weighted average
• expectation — Expected value

Permutations & combinations

• factorial — Factorial
• permutations — Permutations
• choose — Combinations
• permvscomb — Permutation vs Combination

Binomial, Poisson & geometric

• dbinom — Exact binomial probability
• pbinom — Cumulative binomial
• dpois — Exact Poisson probability
• ppois — Cumulative Poisson
• dgeom — Geometric probability
• pgeom — Cumulative geometric

The normal distribution

• dnorm — Height of the curve
• pnorm — Probability below a value
• qnorm — Value for a probability
• scale — Standardize (z-scores)
• rnorm — Random normal samples

Beyond the normal

• normsum — Adding two normals
• normapprox — Normal approximation

Sampling & estimation

• sampbasics — Populations & sampling
• summary — Five-number summary
• quantile — Quantiles
• sampling — Sampling distribution

Confidence intervals

• confint — Confidence interval

Hypothesis testing

• t.test — One-sample t-test
• prop.test — Proportion test

The χ² distribution

• pchisq — Chi-square probability
• chisq.test — Chi-square test

Correlation & regression

• cor — Correlation
• lm — Linear regression

Supervised learning

• knn — k-Nearest Neighbors

Linear regression methods

• ridge — Ridge regression
• lasso — Lasso regression

Classification

• logreg — Logistic regression
• lda — Linear Discriminant Analysis

Basis expansions

• splines — Regression splines

Kernel smoothing

• kernel — Kernel smoothing

Model assessment

• biasvar — Bias–variance trade-off
• crossval — Cross-validation

Model inference

• bootstrap — The bootstrap

Trees

• tree — Decision trees (CART)

Boosting

• boosting — Gradient boosting

Neural networks

• neuralnet — Neural networks

Support vector machines

• svm — Support Vector Machines

Unsupervised learning

• kmeans — k-Means clustering
• pca — Principal Component Analysis

Random forests

• forest — Random forests