Statistics Calculators
Adjusted R-Squared Calculator
Calculate adjusted R-squared from R-squared, sample size, and predictor count to compare regression models fairly, penalizing unnecessary added predictors.
ANOVA Calculator
Calculate the F-statistic and p-value for a one-way ANOVA across multiple groups, illustrated with a worked three-group teaching-method comparison example.
Bayes Theorem Calculator
Apply Bayes' theorem to update a prior probability into a posterior probability using the likelihood of observed evidence under two competing hypotheses.
Binomial Distribution Calculator
Calculate exact, at-least, and at-most probabilities for the binomial distribution, illustrated with a worked quality-control defect-rate inspection example.
Chi-Square Calculator
Calculate the chi-square statistic and p-value for goodness-of-fit or 2x2 independence tests, with a critical-value reference table by degrees of freedom.
Coefficient of Variation Calculator
Calculate the coefficient of variation to compare relative spread across data sets measured on entirely different scales, with a worked side-by-side example.
Coin Flip Calculator
Calculate the exact binomial probability of a given number of heads across any number of coin flips, fair or biased, with the full ten-flip distribution table.
Confidence Interval Calculator
Calculate a confidence interval for a population mean or proportion using the t- or normal distribution, with two fully worked numeric examples included.
Confidence Level Calculator
Convert a Z-score into its corresponding two-tailed confidence level on the standard normal distribution using the normal cumulative distribution function.
Correlation Calculator
Calculate the Pearson correlation coefficient between two variables, with strength interpretation thresholds and a fully worked numeric example and result.
Critical Value Calculator
Find z, t, chi-square, or F critical values for any alpha level and degrees of freedom, using numerical inversion of each distribution's CDF function.
Cronbach's Alpha Calculator
Calculate Cronbach's alpha from a matrix of item responses to measure the internal consistency and reliability of a multi-item survey or test scale used.
Dice Roll Calculator
Calculate the exact probability of rolling any target sum with any number of dice and sides, including the complete two-dice sum probability distribution table.
Effect Size Calculator
Calculate Cohen's d from two sample means, standard deviations, and sample sizes, with an automatic magnitude rating from negligible up through large effect.
Exponential Distribution Calculator
Calculate probability density, cumulative, and survival probabilities for the exponential distribution, with a worked equipment-lifetime reliability example.
F-Test Calculator
Calculate the F-statistic and two-tailed p-value for comparing two sample variances, illustrated with a worked production-line consistency comparison example.
Interquartile Range Calculator
Calculate the interquartile range of a data set using the exclusive median method, with a worked quartile example and the standard 1.5x outlier-detection rule.
Kendall Tau Calculator
Calculate Kendall's tau-b correlation from concordant and discordant pair counts, a rank correlation measure that stays robust to ties and outliers in data.
Kruskal-Wallis Calculator
Run a Kruskal-Wallis H test across three or more independent groups to compare distributions without assuming normality or equal group variance in the data.
Linear Regression Calculator
Fit a least-squares regression line to paired x and y data, returning the slope, intercept, R-squared value, and a prediction for any new x value entered.
Logistic Regression Calculator
Fit a logistic regression model to binary outcome data and predict the probability of a positive outcome at any given input value along the fitted curve.
Mann-Whitney U Test Calculator
Run a Mann-Whitney U test on two independent samples to compare distributions without assuming normality, returning the U statistic, z-score, and p-value.
Margin of Error Calculator
Calculate the margin of error for a sample mean from the standard deviation, sample size, and confidence level using the standard z-based margin formula.
McNemar Calculator
Run McNemar's test on paired binary outcomes using discordant pair counts b and c, with automatic continuity correction applied for small sample sizes.
Mean Calculator
Calculate the arithmetic mean of any data set and see how outliers can pull the average away from the typical value, illustrated with a worked salary example.
Median Absolute Deviation Calculator
Calculate the median absolute deviation, an outlier-resistant spread measure, with a worked comparison showing how it holds up against standard deviation.
Median Calculator
Find the middle value of a data set with a calculator that resists outliers, plus a worked example comparing the median directly against the arithmetic mean.
Odds Ratio Calculator
Calculate the odds ratio and confidence interval for a 2x2 exposure-outcome table, illustrated with a worked case-control epidemiology study example and result.
P-Value Calculator
Find the p-value from a z-score, t-score, chi-square statistic, or F-statistic, with one-tailed and two-tailed options for standard hypothesis testing.
Paired T-Test Calculator
Run a paired t-test on before and after measurements from the same subjects to test whether the average difference is significantly different from zero.
Pearson Correlation Calculator
Calculate Pearson's correlation coefficient r between two numeric variables, with significance testing and a strength-of-relationship interpretation included.
Poisson Distribution Calculator
Calculate exact, at-least, and at-most probabilities for the Poisson distribution, illustrated with a worked call-center hourly arrival-rate example and table.
Power Calculator
Estimate the statistical power of a two-sample test from effect size, sample size per group, and significance level using the z-test approximation formula.
Probability Calculator
Calculate basic, complement, and/or, and conditional probabilities with the exact formula for each of six scenarios, plus reference probability benchmarks
Probability of Success Calculator
Calculate binomial probabilities for exactly, at least, at most, or between k successes across n independent trials with a fixed success probability value.
R-Squared Calculator
Calculate R-squared from a correlation coefficient or from actual versus predicted data to see how much variance a regression model actually explains.
Range Calculator
Calculate the range between the maximum and minimum values in a data set, with guidance on when a more robust spread measure like IQR is worth using instead.
Regression Calculator
Calculate the least-squares linear regression equation, R-squared, and predicted values from paired X and Y data, with a fully worked example included.
Relative Risk Calculator
Compute relative risk and its confidence interval from a 2x2 exposure table, using the log-scale formula standard in cohort studies and clinical trials data.
Relative Standard Deviation Calculator
Calculate relative standard deviation (RSD) as a percentage of the mean from a list of values, a scale-independent measure of dataset spread and variability.
Sample Size Calculator
Determine the survey sample size needed for a target confidence level and margin of error using Cochran's formula, with a reference table of common settings.
Sample Size for Mean Calculator
Determine the minimum sample size needed to estimate a population mean within a target margin of error, given the population's standard deviation value.
Sample Size for Proportion Calculator
Determine the minimum sample size to estimate a population proportion within a target margin of error at 90 percent, 95 percent, or 99 percent confidence level.
Spearman Rank Correlation Calculator
Calculate Spearman's rank correlation coefficient rho between two variables to detect monotonic relationships that aren't strictly linear in shape or form.
Standard Deviation Calculator
Calculate sample or population standard deviation with both formulas explained side by side, plus an empirical-rule reference table for normal distributions.
Standard Error Calculator
Calculate the standard error of a sample mean from raw data or from a known standard deviation and sample size, with a sample-size shrinkage reference table.
Standard Normal Distribution Calculator
Calculate cumulative, density, interval, and inverse probabilities for the standard normal distribution, with a reference table of z-values and percentiles
T-Test Calculator
Calculate the t-statistic and p-value for one-sample, two-sample, or paired t-tests, with a worked height example and a critical t-value reference table.
Uniform Distribution Calculator
Calculate probabilities for continuous or discrete uniform distributions, with worked mean, variance, and probability examples covering both distribution types.
Variance Calculator
Calculate sample or population variance with both formulas shown side by side and a worked example comparing the two results on the exact same data set.
Welch's T-Test Calculator
Run Welch's t-test on two independent samples without assuming equal variances, using the Welch-Satterthwaite degrees of freedom adjustment formula each time.
Wilcoxon Signed-Rank Calculator
Run a Wilcoxon signed-rank test on paired before and after measurements to detect a shift when the differences aren't normally distributed across pairs.
Z-Score Calculator
Convert any raw value into a standardized z-score using the mean and standard deviation, with a cumulative-probability percentile reference table included.
Z-Test Calculator
Run a one-sample or two-sample z-test using known population standard deviations, with one-tailed and two-tailed p-value options included in the result.
The Formulas Behind Every Statistics Course and Research Paper
Statistics calculations underpin both classroom coursework and real research — the same t-test, chi-square test, or confidence interval formula that appears on a homework set is the one used to validate findings in published studies. More than fifty calculators here cover descriptive statistics, hypothesis testing, probability distributions, and regression analysis.
Popular Statistics Calculators
Highlights across hypothesis testing, distributions, and regression:
- Confidence Interval Calculator — calculates a range likely to contain a population parameter given sample data and a confidence level.
- P-Value Calculator — calculates the probability of observing a result at least as extreme as the data, assuming the null hypothesis is true.
- Linear Regression Calculator — fits a best-fit line to paired data and reports slope, intercept, and fit statistics.
- Chi-Square Calculator — tests whether observed categorical frequencies differ significantly from expected frequencies.
- Standard Deviation Calculator — calculates how spread out a dataset is around its mean.
Why a Small P-Value Doesn't Mean What Many People Assume
A p-value below the common 0.05 threshold is often described as "statistically significant," but it specifically measures the probability of the observed data (or something more extreme) occurring if the null hypothesis were true — it does not measure the probability that the null hypothesis itself is true, nor does it measure the size or importance of an effect. This distinction matters because a large enough sample size can make even a tiny, practically meaningless difference statistically significant, which is exactly why researchers increasingly report effect size alongside p-value rather than treating statistical significance alone as proof of a meaningful finding.
Frequently Asked Questions
What's the difference between a confidence interval and a p-value?
A p-value tests a specific hypothesis and gives a single probability figure, while a confidence interval gives a range of plausible values for a parameter, providing more information about both the size and the precision of an estimate.
Why do some statistical tests require normally distributed data?
Many classical tests (like the standard t-test) derive their probability calculations assuming a normal distribution; when that assumption is badly violated, non-parametric alternatives (like Mann-Whitney U) are typically used instead.
Explore More
Applying statistics to model evaluation? See the Data Science Calculators, or check probability-heavy game math in the Casino & Gambling Calculators.