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.