Regression Analysis provides complete coverage of the classical methods of statistical analysis. It is designed to give students an understanding of the purpose of statistical analyses, to allow the student to determine, at least to some degree, the correct type of statistical analyses to be performed in a given situation, and have some appreciation of what constitutes good experimental design.
Examples and exercises contain real data and graphical illustration for ease of interpretation Outputs from SAS 7, SPSS 7, Excel, and Minitab are used for illustration, but any major statistical software package will work equally well
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Examples and exercises contain real data and graphical illustration for ease of interpretation Outputs from SAS 7, SPSS 7, Excel, and Minitab are used for illustration, but any major statistical software package will work equally well
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
"...is well-written , well-organized, and succeeds in making regression analysis understandable, without being overly technical." --Donice McCune, Stephen F. Austin University
"I would say that this book is excellent from both a pedagogical perspective and a learning perspective (by the student). The instructor will enjoy discussing various concepts and then illustrating the concepts through the thorough examples. 6. This textbook will help give the students additional mathematical maturity for handling other statistics courses, especially applied courses like Analysis of Variance." --Steven Garren, James Madison University
"I would say that this book is excellent from both a pedagogical perspective and a learning perspective (by the student). The instructor will enjoy discussing various concepts and then illustrating the concepts through the thorough examples. 6. This textbook will help give the students additional mathematical maturity for handling other statistics courses, especially applied courses like Analysis of Variance." --Steven Garren, James Madison University