Sample from uniform, skewed, or Bernoulli populations and watch the sampling distribution of the mean emerge.
Open →Calculate and visualize 90%, 95%, or 99% confidence intervals from sample summary statistics.
Open →Analyze a 2×2 contingency table, inspect expected counts, and interpret the chi-square p-value.
Open →Add data points, draw a scatter plot, and fit a linear regression line.
Enter a data set and instantly calculate mean, median, mode, variance, standard deviation, quartiles, histogram, and box plot.
Switch between normal, binomial, and Poisson distributions, then compare their shape and summary values.
Run a one-sample z-test or t-test, visualize the rejection region, and compare the p-value with alpha.
View summary cards, trend charts, and compact data tables in a dashboard layout.
Resample a data set and visualize a bootstrap distribution with a confidence interval.
Adjust prevalence, sensitivity, and specificity to see how diagnostic test results change.