- Introduction Introduces the toolbox, and explains the mathematical notation it uses.
- Probability Distributions Describes the distributions and the distribution-related functions supported by the toolbox.
- Descriptive Statistics Explores toolbox features for working with descriptive statistics such as measures of location and spread, percentile estimates, and data with missing values.
- Linear Models Describes toolbox support for one-way, two-way, and higher-way analysis of variance (ANOVA), analysis of covariance (ANOCOVA), multiple linear regression, stepwise regression, response surface prediction, ridge regression, and one-way multivariate analysis of variance (MANOVA). It also describes support for nonparametric versions of one- and two-way ANOVA, and multiple comparisons of the estimates produced by ANOVA and ANOCOVA functions.
- Nonlinear Regression Models Discusses parameter estimation, interactive prediction and visualization of multidimensional nonlinear fits, and confidence intervals for parameters and predicted values.
- Hypothesis Tests Describes support for common tests of hypothesis - t-tests, Z-tests, nonparametric tests, and distribution tests.
- Multivariate Statistics Explores toolbox features that support methods in multivariate statistics, including principal components analysis, factor analysis, one-way multivariate analysis of variance, cluster analysis, and classical multidimensional scaling.
- Statistical Plots Describes box plots, normal probability plots, Weibull probability plots, control charts, and quantile-quantile plots which the toolbox adds to the arsenal of graphs in MATLAB. It also discusses extended support for polynomial curve fitting and prediction, creation of scatter plots or matrices of scatter plots for grouped data, interactive identification of points on such plots, and interactive exploration of a fitted regression model.
- Statistical Process Control Discusses the plotting of common control charts and the performing of process capability studies.
- Design of Experiments Discusses toolbox support for full and fractional factorial designs, response surface designs, and D-optimal designs. It also describes functions for generating designs, augmenting designs, and optimally assigning units with fixed covariates.
- Demos Describes GUIs that enable you to explore the probability distributions, random number generation, curve fitting, and design of experiments functions.
- The Release Notes summarize new features, bug fixes, etc.

** Finding Functions**

Browse functions by following these links:

Printable versions of Statistics Toolbox User's Guide and Statistics Toolbox Release Notes are available in PDF format.

The MathWorks provides several related products relevant to the tasks you can perform with the Statistics Toolbox.