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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

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min Minimum elements of an array
mink Findksmallest elements of array
max Maximum elements of an array
maxk Findk最大的数组元素
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.