Statistics Tools

Enter a dataset to see mean, median, and mode on an interactive number line with a balance-point fulcrum, box plot, and step-by-step calculations.

Compute mean, median, mode, standard deviation, and more. Visualize data with interactive box plots and histograms.

Find the best-fit line for paired data. See slope, intercept, correlation, R-squared, scatter plot, and residual analysis.

Explore normal, binomial, Poisson, and uniform distributions. Visualize PDF/CDF plots, compute probabilities with draggable bounds, and find inverse values.

Run z-tests, t-tests, two-sample t-tests, and chi-square goodness-of-fit tests. See test statistics, p-values, critical values, and step-by-step breakdowns.

Calculate confidence intervals for means (z and t) and proportions. See margin of error, critical values, number line visualization, and sample size calculations.

Interactive bell curve with shaded probability regions. Convert between raw scores and Z-scores with numerical integration.

Compute posterior probability with an SVG tree diagram, contingency table, and natural frequency display. Step-by-step Bayes formula.

One-way ANOVA for comparing 2-6 group means. F-statistic, p-value, effect size, summary table, and side-by-side box plots.

Test independence with contingency tables up to 4x4. Chi-square statistic, p-value, Cramer's V, and grouped bar chart.

Enter any dataset to compute quartiles, IQR, five-number summary, and percentile ranks. Visualize the distribution with an interactive dot plot.

Build side-by-side box plots for up to three datasets. Shows Q1, median, Q3, Tukey whiskers, and outlier detection.

Plot x,y data pairs to visualize relationships. Computes Pearson correlation coefficient, r-squared, and fits a linear regression line.

Draw repeated samples from non-normal populations and watch the sampling distribution become normal. Side-by-side histograms.

Fit linear, quadratic, cubic, exponential, logarithmic, and power models to data. Compare R-squared, residuals, and predict new values with scatter plots.

Enter data and build picture graphs, bar graphs, and line plots. Auto-generated questions test reading and comparing data. Perfect for elementary data literacy

Create line plots from measurement data using fractions. Place X marks on number lines with halves, fourths, and eighths. Answer questions and compute totals from fraction data.

Spin a colorful spinner or roll a die, track your results, and explore what is more likely or less likely to happen. Grades 3-5.

Compute uncertainty propagation through experimental formulas. Choose from sum, difference, product, quotient, power, log, exponential, or generic two-variable presets. See the full propagation formula in KaTeX with partial derivatives. Repeated-measurement mode computes mean, sample standard deviation, standard error of the mean, 95% confidence interval, and a histogram from a list of measurements. Output is rounded to match the leading uncertainty digit (e.g. 12.34 plus or minus 0.05).

Visualize how gradient descent finds the best-fit line on a 2D scatter dataset. Drag points, adjust slope and intercept manually with sliders, or click train to animate gradient descent for ~150 iterations. Live readouts of MSE, R-squared, and distance from the closed-form OLS optimum. Loss curve mini-plot tracks MSE over iterations. Five preset datasets including outlier-corrupted and heteroscedastic data show OLS assumptions and limits.