SciPy Statistical Functions Last Updated : 23 Jun, 2025 Summarize Comments Improve Suggest changes Share Like Article Like Report SciPy provides a comprehensive set of statistical functions in its scipy.stats module. These tools are important for performing descriptive statistics, statistical testing, probability distributions and random variable operations in scientific and data analysis workflows.The following table summarizes key statistical functions in SciPyFunctionDescriptionMean() Calculates the average of a dataset by summing all values and dividing by the number of values.Mode() Finds the most frequent value(s) in a dataset.Median() Identifies the middle value in a sorted dataset.standard deviationMeasures the spread of data points around the meanharmonic meanCalculates the reciprocal of the average of the reciprocals, useful for rates.varianceA measure of spread, calculated as the average squared deviation from the mean.standard errorThe standard deviation of a sampling distribution, indicating variability.percentileA value below which a given percentage of observations fallskewness Measures the asymmetry of a distributionlog-logistic distributionModels survival data and is used in reliability analysis.Student’s t DistributionEstimates population parameters when the sample size is small..kurtosis (Fisher or Pearson)Measures the "tailedness" of a distribution.Z-scoreMeasures how many standard deviations a data point is from the mean.coefficient of variationRatio of the standard deviation to the mean, used to measure variability.cumulative frequencyShows the running total of frequencies in a dataset.Continuous Random Variable A random variable that can take any value within a range (e.g., height, weight, temperature).gamma continuous random variableUsed to model waiting times or life durations. exponential continuous random variableModels time between events in a Poisson process.generalized exponential continuous random variableFlexible for modeling data with additional shape parameters.alpha continuous random variableOften related to the shape parameter in various probability distributions.Erlang continuous random variableA special case of the Gamma distribution, used in queuing theory.chi continuous random variableUsed in hypothesis testing, particularly the Chi-squared test.Uniform continuous random variableAll outcomes within a range are equally likely.Half-logistic continuous random variableA variant of the logistic distribution, limited to positive values.arcsine continuous random variableModels the arcsine of a variable, often used for angle-related data.Half-Cauchy continuous random variableSimilar to Cauchy but restricted to positive values, often used in Bayesian statistics.cosine continuous random variableBased on the cosine function, used in circular data applications.Frechet left ( Weibull maximum)Models the maximum values in a dataset, like the largest daily rainfall.Related Article:Statistics in SciPyOptimization in SciPyIntegration in SciPyData Analysis with SciPy Comment More infoAdvertise with us Next Article SciPy Statistical Functions K kareeen0d5l Follow Improve Article Tags : Data Science Library AI-ML-DS With Python Data Science Similar Reads Linear Regression in Machine learning Linear regression is a type of supervised machine-learning algorithm that learns from the labelled datasets and maps the data points with most optimized linear functions which can be used for prediction on new datasets. 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