Documentation

Descriptive Statistics

Range, central tendency, standard deviation, variance, correlation

Descriptive statistics quantitatively describe features of a sample of data, such as the basic mean or standard deviation. Cumulative methods report a statistic as you move through the elements of an array. Moving methods report a statistic within a local window of array elements, then move to the next window.

Functions

expand all

 min Minimum elements of an array mink Find k smallest elements of array max Maximum elements of an array maxk Find k largest elements of array bounds Smallest and largest elements topkrows Top rows in sorted order mean Average or mean value of array median Median value of array mode Most frequent values in array std Standard deviation var Variance corrcoef Correlation coefficients cov Covariance xcorr Cross-correlation xcov Cross-covariance
 cummax Cumulative maximum cummin Cumulative minimum
 movmad Moving median absolute deviation movmax Moving maximum movmean Moving mean movmedian Moving median movmin Moving minimum movprod Moving product movstd Moving standard deviation movsum Moving sum movvar Moving variance

Topics

Computing with Descriptive Statistics

Analyze data with basic statistics.

Inconsistent Data

Identify outliers within data sets.

Linear Correlation

Covariance and correlation coefficients help to describe the linear relationship between variables.

Linear Regression

Least squares fitting is a common type of linear regression that is useful for modeling relationships within data.

Interactive Fitting

The Basic Fitting UI is an interactive data modeling tool.

Programmatic Fitting

There are many functions in MATLAB® that are useful for data fitting.