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Using MATLAB® for Statistical Analysis

  • Yuri A. W. Shardt

Abstract

This chapter introduces the reader to the application of MATLAB® to solving statistical problems. Appropriate MATLAB functions for visualising data, performing regression analysis, design and analysis of experiments, time series analysis, and system identification are presented drawn from the available toolboxes, including the statistical, system identification, and econometric toolboxes. MATLAB code that can create periodograms, autocorrelation plots, correlation plots, and cross-correlation plots is provided. Three detailed examples, covering linear regression, nonlinear regression, and system identification are presented to provide the reader with appropriate code and an approach to these problems in MATLAB. By the end of this chapter, the reader should be comfortable in using MATLAB to solve any of the problems presented in this book and be able to prepare properly labelled figures.

Keywords

Nonlinear Regression Modern Approach Correlation Plot Linear Regression Problem Book Statistics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Yuri A. W. Shardt
    • 1
  1. 1.Institute of Automation and Complex Systems (AKS)University of Duisburg-EssenDuisbergGermany

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