Data Analysis Methods - Research Achievements of the 15th National Planning Project in Educational Science

Author: Mei Changlin
Publisher:
Publish Date: 2006-02-01
Features: This textbook is written for undergraduate students majoring in Information and Computational Science at universities, for their "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 relevant SAS procedures related to the above methods, facilitating the practical application of each method. Each chapter is equipped with a wealth of exercises with real-world application backgrounds. This book can also serve as a textbook for undergraduate students majoring in statistics at universities and non-mathematics master's students, as well as a reference book for data analysts. ... The content of this book 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.