Mathematics

# Data Analysis and Statistics

This chapter introduces the MATLAB data analysis capabilities. It includes the following topics:
 Column-Oriented Data Sets Organizing arrays for data analysis. Basic Data Analysis Functions Basic data analysis functions and an example that uses some of the functions. This section also discusses functions for the computation of correlation coefficients and covariance, and for finite difference calculations. Data Preprocessing Working with missing values, and outliers or misplaced data points in a data set. Regression and Curve Fitting Investigates the use of different regression methods to find functions that describe the relationship among observed variables. Case Study: Curve Fitting Uses a case study to look at some of the MATLAB basic data analysis capabilities. This section also provides information about the Basic Fitting interface. Difference Equations and Filtering Discusses MATLAB functions for working with difference equations and filters. Fourier Analysis and the Fast Fourier Transform (FFT) Discusses Fourier analysis in MATLAB.

Data Analysis and Statistics Functions

The data analysis and statistics functions are in the directory `datafun` in the MATLAB Toolbox. Use online help to get a complete list of functions.

Related Toolboxes

A number of related toolboxes provide advanced functionality for specialized data analysis applications.

 Toolbox Data Analysis Application Optimization Nonlinear curve fitting and regression. Signal Processing Signal processing, filtering, and frequency analysis. Spline Curve fitting and regression. Statistics Advanced statistical analysis, nonlinear curve fitting, and regression. System Identification Parametric / ARMA modeling. Wavelet Wavelet analysis.

 Selected Bibliography Column-Oriented Data Sets