Advanced statistical analysis tools for data science, research, and probability.
Measure how much two variables change together.
Calculate the average, minimum, and maximum rolls for RPG dice notation.
Calculate the average of rates or ratios effectively.
Measure the spread of the middle 50% of your data, ignoring extreme outliers.
Calculate the averaged value for exponentially changing rates or flow gradients.
Measure the average squared difference between estimated and actual values.
Calculate central tendency measures for your dataset.
Calculate the robust measure of statistical dispersion.
Find the exact midpoint between your lowest and highest values.
Calculate the value below which a given percentage of data falls.
Calculate the weighted average of standard deviations for two groups with different sample sizes.
Analyze how your data is distributed by splitting it into four equal parts.
Calculate the difference between the maximum and minimum values.
Measure the asymmetry of your data distribution.
Measure the dispersion or spread of your dataset.
Calculate sample or population variance and standard deviation.
Calculate averages where some values carry more importance than others.
Calculate the 'true' rating score using the Wilson Score Interval.
Determine if your test results are statistically significant.
Convert between Absolute (± unit) and Relative (%) uncertainty.
Evaluate model fit while accounting for the number of predictors.
Update the probability of a hypothesis as more evidence or information becomes available.
Audit numerical datasets for natural conformity using leading digit analysis.
Adjust significance level for multiple comparisons.
A famous probability puzzle about conditional probability.
Visualize how sample means form a Normal distribution.
Universal probability bounds for any distribution with a defined mean and variance.
Calculate the ideal class width for frequency distributions.
Measure the goodness-of-fit for your regression model.
Measure the relative variability of a dataset compared to its mean.
Calculate the standardized difference between two means to measure effect size.
Simulate coin flips and track streak statistics.
Calculate the number of ways to choose items from a set.
Calculate the constant ratio between two proportional quantities.
Find Z and T critical values for hypothesis testing.
Partition your dataset into ten equal parts to analyze distribution.
Roll generic or custom dice for games and probabilities.
Calculate Normal Distribution coverage bands (68-95-99.7 rule).
Special function occurring in probability, statistics, and diffusion equations.
Calculate uncertainty for arithmetic operations on measured values.
Calculate the long-term average outcome of a random variable.
Compare the variances of two independent populations to see if they are significantly different.
Understand why high-accuracy tests can still produce mostly false positives.
Analyze frequency distribution with tables and polygon charts.
Measure income or wealth inequality within a population.
Calculate mean, variance, and standard deviation for grouped frequency data.
Compare the means of two independent groups to determine if they are significantly different.
Measure the variability of categorical (nominal) data variables.
Determine if a sample follows a specific probability distribution.
Calculate the probability of winning the lottery.
Compare two independent groups to see if they come from the same distribution without assuming normality.
The most robust metric for evaluating classification models, especially on imbalanced datasets.
Statistical test for paired nominal data to determine significant changes in proportions.
Instantly find the smallest and largest values in your dataset, along with total range and distribution.
Convert American odds to implied probability and various international formats.
Compare a sample mean to a known population mean.
Compare a sample mean to a known population mean with a known standard deviation.
Instantly sort and organize numerical datasets for further analysis.
Identify anomalous data points using Tukey's Fences method.
Determine the statistical significance of your results.
Two losing games can combine to form a winning game.
Calculate point estimates for Population Mean or Population Proportion.
Measure how well a manufacturing process meets specifications.
Calculate absolute and relative error with percentage values.
Analyze how often items occur in a dataset relative to the total number of items.
Compare the likelihood of events between two different groups.
Calculate payouts and winning probabilities for Roulette setups.
Calculate point estimates and confidence intervals for population proportions.
Calculate the margin of error for survey results.
Evaluate the performance of a diagnostic test or binary classifier.
Measure the information content and unpredictability of a data source.
Determine the precision of your sample mean compared to the population mean.
Calculate the standard error of the mean for hypothesis testing.
Look up probabilities and critical values for the T-distribution.
Calculate Total (SST) or Residual (SSR) Sum of Squares.
Should you switch envelopes if one contains twice the money of the other?
Calculate UCL and LCL for Statistical Process Control (SPC).
Analyze the relationships and intersections between two sets of data.
Calculate Youden's Index to evaluate the performance of a binary classifier.
Standardize your data points and find their relative position.
Find the area under the standard normal curve for any Z-score, representing cumulative probability.
A counter-intuitive probability puzzle involving three boxes.
A problem showing how different methods of random selection yield different probabilities.
Calculate the surprising probability that two people in a group share the same birthday.
Simulate the famous probability paradox to see why switching doors is always better.
Calculate species diversity and community dominance.
Visualize the Beta distribution and calculate its properties.
Calculate probabilities for independent binary trials.
Determine if observed data matches an expected distribution.
Determine if there is a significant relationship between two categorical variables.
Model the time between independent events occurring at a constant average rate.
Calculate future value based on exponential growth.
Fit an exponential curve (y = ae^bx) to your data.
Convert raw data into a comprehensive frequency distribution table.
Calculate probabilities for the number of trials needed to get the first success.
Calculate the average of a set of products, ideal for growth rates and ratios.
Probability distribution for sampling without replacement from a finite population.
Statistical model for random variables whose logarithms are normally distributed.
Calculate the probability of failures before a target number of successes.
Approximate binomial probabilities using the normal distribution.
Analyze probabilities and densities of the most common statistical distribution.
Easily switch between odds (e.g., 4:1) and their implied probability (20%).
Model the probability of rare events in a fixed interval.
Calculate the probability of independent events occurring.
Model the magnitude of vectors and stochastic systems like wind speed and signal fading.
Calculate the joint probability of three independent events occurring together.
Calculate the probability of rolling a specific sum with two six-sided dice.
Analyze distributions where every outcome in a given range is equally likely.
The 'Swiss Army Knife' of failure analysis, capable of modeling infant mortality, random failures, and wear-out.
Measure the linear relationship between two datasets.
Fit non-linear curves to your data to capture complex trends.
Calculate residuals, SSE, and visualize errors.
Predict trends and analyze relationships between variables.
Measure the monotonic relationship between two variables using their ranks.
Estimate the range where a population parameter likely falls.
Exact significance test for 2x2 contingency tables, ideal for small sample sizes.
Compare means across three or more independent groups to find statistical significance.
Calculate the statistical power of a test given sample size and effect.
Calculate the number of respondents needed for a survey.
Generate five-number summary and box plot visualizations.
Visualize data frequency using a dot plot.
Create a frequency distribution histogram from data.
Visualize categorical data proportions with a beautiful circular plot.
Visualize data distributions while keeping every raw value visible.
