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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.


alle erweitern

minMinimum elements of an array
minkFind k smallest elements of array
maxMaximum elements of an array
maxkFind k largest elements of array
boundsMinimum and maximum values of an array
topkrowsTop rows in sorted order
meanAverage or mean value of array
medianMedian value of array
modeMost frequent values in array
stdStandard deviation
corrcoefCorrelation coefficients
cummaxCumulative maximum
cumminCumulative minimum
movmadMoving median absolute deviation
movmaxMoving maximum
movmeanMoving mean
movmedianMoving median
movminMoving minimum
movprodMoving product
movstdMoving standard deviation
movsumMoving sum
movvarMoving variance


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.