Data analysis methods

Author: Mei Changlin
Publisher:
Publish Date: 2006-02-01
Features: This book is written as a textbook for undergraduate students of information and computing science majors in universities, for the "Data Analysis Course." It covers the basic content and methods of common statistical data analysis, including descriptive data analysis, linear regression analysis, analysis of variance, principal component analysis and canonical correlation analysis, discriminant analysis, cluster analysis, and Bayesian statistical analysis. Additionally, it provides an introduction to the basic content of SAS software and SAS procedures related to the above content to facilitate the practical application of each method. Each chapter is equipped with a rich set of exercises with practical application backgrounds. This book can also serve as a textbook for undergraduate students of statistics majors in universities and non-mathematics master's students, as well as a reference book for data analysts.