Calculators

Finds the Z-score corresponding to a given cumulative probability (percentile) on a normal distribution.

Performs a t-test (one-sample, two-sample, or paired) to compare means and determine statistical significance.

Calculates the standard error, which measures the accuracy with which a sample represents a population. It's commonly used for the standard error of the mean (SEM) and the standard error of the proportion.

Identifies potential outliers in a dataset using the IQR * 1.5 rule (calculating fences).

Calculates the Chi-Square statistic and p-value for goodness-of-fit or test of independence. It requires observed and expected frequencies or values.

Calculates the pooled standard deviation, an estimate of the standard deviation for two samples assuming equal variance, often used in two-sample t-tests.

Calculates the accuracy of a classification model based on True Positives (TP), True Negatives (TN), False Positives (FP), and False Negatives (FN). Accuracy is the proportion of correct predictions over the total number of predictions.

Calculates the probability of observing a test statistic as extreme as, or more extreme than, the one calculated, assuming the null hypothesis is true.

Calculates the average of the absolute differences between each data point and the mean.

Calculates probabilities related to the time until an event occurs in a Poisson process. The exponential distribution models the time until an event happens, given an average rate of occurrence.