Examples for

Descriptive Statistics

Descriptive statistics are statistical measures of a dataset that describe, characterize and summarize its properties, such as shape, variability, size and central location. Wolfram|Alpha's rigorous statistical algorithms enable you to compute and characterize the properties of your data with lightning-fast speed.

Summary Statistics

Compute elementary descriptive statistics summarizing the properties of a dataset, such as maximum and minimum values or number of entries.

Calculate basic descriptive statistics for a dataset:

Measures of Dispersion

Compute the measures of dispersion, such as variance or standard deviation, for a dataset.

Compute the variance:

Compute the standard deviation:

Measures of Central Tendency

Compute common measures of central tendency, such as mean, median and mode, for a dataset.

Compute the mean of a dataset:

Compute the median:

Compute the geometric mean:

Other Descriptive Statistics

Compute other common descriptive statistics, such as skewness, kurtosis and outliers, for a dataset.

Compute the skewness:

Compute the kurtosis:

Determine the outliers for a dataset: