Statistics Calculators

Calculate different types of means including arithmetic, geometric, and harmonic means. Understand which average is best for your data.

Calculate the median of your data set. The median is the middle value that separates the higher half from the lower half of your data.

Calculate the mode of a dataset - the value that appears most frequently.

Calculate the range of your dataset to measure the spread between the minimum and maximum values.

Calculate the standard deviation of your dataset to measure how spread out the values are from the mean.

Calculate the variance of your dataset to measure how spread out the values are from the mean.

Calculate the coefficient of variation to measure relative variability. Compare variation between datasets with different units or means.

Calculate the mean absolute deviation of your dataset to measure the average distance of values from the mean.

Calculate the median absolute deviation of your dataset for a robust measure of statistical dispersion that is less sensitive to outliers.

Calculate z-scores to standardize your data and determine how many standard deviations a value is from the mean.

Calculate the Sum of Squared Errors (SSE) for your dataset. Measure the total squared deviation from the mean for statistical analysis.

Calculate probabilities and z-scores for normal distributions. Perfect for statistical analysis and probability calculations.

Calculate probabilities for binary outcome events using the binomial distribution. Perfect for analyzing success/failure scenarios and probability distributions.

Calculate probabilities for events occurring in a fixed interval using the Poisson distribution. Perfect for analyzing rare events and counting processes.

Perform chi-square tests for independence and goodness of fit. Analyze categorical data relationships and compare observed vs expected frequencies.

Perform one-way Analysis of Variance (ANOVA) to compare means across multiple groups. Test for significant differences between group means with statistical visualization.

Calculate confidence intervals for population means. Estimate population parameters with specified confidence levels using sample data.

Calculate critical values for various statistical distributions including Normal, t, Chi-square, and F distributions.

Calculate degrees of freedom for various statistical tests including t-tests, ANOVA, and chi-square tests

Calculate the five number summary (minimum, Q1, median, Q3, maximum) of your dataset. Perfect for understanding data distribution and identifying key statistical points.

Calculate quartiles to divide your dataset into four equal parts.

Calculate the interquartile range (IQR) and identify outliers in your data. Perfect for understanding data spread and detecting unusual values.

Calculate both kurtosis and relative kurtosis (excess kurtosis) to measure the relative weight of your distribution's tails. Identify if your data has more or fewer extreme values compared to a normal distribution.

Calculate percentiles to determine the position of a value within a dataset.

Calculate a comprehensive statistical summary of your dataset including mean, median, mode, standard deviation, and more.

Calculate Pearson correlation coefficient (r) to measure the strength and direction of linear relationships between two variables. Includes statistical significance testing and R² analysis.

Calculate the coefficient of determination (R²) to measure how well a regression model fits your data. Includes adjusted R² and visual analysis.

Calculate covariance to measure how two variables change together. Analyze the direction and magnitude of relationships between paired measurements.