Introduction to Genstat for Windows PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Introduction to Genstat for Windows PDF full book. Access full book title Introduction to Genstat for Windows by . Download full books in PDF and EPUB format.
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 26
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 26
Get Book Here
Book Description
Author:
Publisher:
ISBN: 9781904375081
Category : Genstat (Computer system)
Languages : en
Pages : 336
Get Book Here
Book Description
Author: R. W. Payne
Publisher:
ISBN: 9781904375210
Category : Genstat (Computer system)
Languages : en
Pages : 343
Get Book Here
Book Description
Author:
Publisher:
ISBN: 9781904375067
Category : Genstat (Computer system)
Languages : en
Pages : 0
Get Book Here
Book Description
Author: R. W. Payne
Publisher:
ISBN: 9781904375241
Category : Genstat (Computer system)
Languages : en
Pages : 354
Get Book Here
Book Description
Author: Peter Lane
Publisher:
ISBN: 9781852061340
Category : Genstat (computer systems)
Languages : en
Pages : 153
Get Book Here
Book Description
Author: P. W. Lane
Publisher:
ISBN: 9781852061289
Category :
Languages : en
Pages :
Get Book Here
Book Description
Author: K. J. McConway
Publisher: Wiley
ISBN: 9780340759851
Category : Mathematics
Languages : en
Pages : 512
Get Book Here
Book Description
This core text is a self-contained course in statistics, covering both the general linear model (including regression and analysis of variance) and the generalized linear model. The authors review the prerequisite methods and ideas in a concise and clear way, and the material is application-oriented, with the software package GENSTAT for Windows integrated into the text. The basics of GENSTAT are introduced, then used in conjunction with a review of simple linear regression, moving on to more sophisticated analyses, such as multiple linear regression, analysis of variance, logistic regression and loglinear modelling. The final chapter consists of four data analysis case studies using techniques drawn from the whole of the book.
Author: Nicholas W. Galwey
Publisher: John Wiley & Sons
ISBN: 1118861825
Category : Mathematics
Languages : en
Pages : 580
Get Book Here
Book Description
Mixed modelling is very useful, and easier than you think! Mixed modelling is now well established as a powerful approach to statistical data analysis. It is based on the recognition of random-effect terms in statistical models, leading to inferences and estimates that have much wider applicability and are more realistic than those otherwise obtained. Introduction to Mixed Modelling leads the reader into mixed modelling as a natural extension of two more familiar methods, regression analysis and analysis of variance. It provides practical guidance combined with a clear explanation of the underlying concepts. Like the first edition, this new edition shows diverse applications of mixed models, provides guidance on the identification of random-effect terms, and explains how to obtain and interpret best linear unbiased predictors (BLUPs). It also introduces several important new topics, including the following: Use of the software SAS, in addition to GenStat and R. Meta-analysis and the multiple testing problem. The Bayesian interpretation of mixed models. Including numerous practical exercises with solutions, this book provides an ideal introduction to mixed modelling for final year undergraduate students, postgraduate students and professional researchers. It will appeal to readers from a wide range of scientific disciplines including statistics, biology, bioinformatics, medicine, agriculture, engineering, economics, archaeology and geography. Praise for the first edition: “One of the main strengths of the text is the bridge it provides between traditional analysis of variance and regression models and the more recently developed class of mixed models...Each chapter is well-motivated by at least one carefully chosen example...demonstrating the broad applicability of mixed models in many different disciplines...most readers will likely learn something new, and those previously unfamiliar with mixed models will obtain a solid foundation on this topic.”—Kerrie Nelson University of South Carolina, in American Statistician, 2007
Author: Jan Lepš
Publisher: Cambridge University Press
ISBN: 9780521891080
Category : Computers
Languages : en
Pages : 296
Get Book Here
Book Description
Table of contents
