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Book Categories |
Chapter 1 Introduction
Chapter 2 Regression
Chapter 3 Analysis of Variance for Balanced Data
Chapter 4 Analyzing Data with Random Effects
Chapter 5 Unbalanced Data Analysis: Basic Methods
Chapter 6 Understanding Linear Models Concepts
Chapter 7 Analysis of Covariance
Chapter 8 Repeated-Measures Analysis
Chapter 9 Multivariate Linear Models
Chapter 10 Generalized Linear Models
Chapter 11 Examples of Special Applications
References
Index
| Price | Condition | Delivery | Seller | Action |
| $99.99 | Digital |
| WonderClub |
Michael Radcliffe
reviewed Sas .For Linear Models on October 17, 2014 Sas .For Linear Models
An absolutely essential book for representation theory. Well translated etc, the only thing I would say is a fair few of the proofs are needlessly complicated. For instance, I remember early on a proof where we have to prove something for all finite dimensional vector spaces, which one would naturally do by induction starting from a line and working upwards. However, Serre insists on this very obtuse proof in strong induction, starting from the 0 vector space? Very weird.
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Add Sas .For Linear Models, This clear and comprehensive guide provides everything you need for powerful linear model analysis. Using a tutorial approach and plenty of examples, the authors lead you through methods related to analysis of variance with fixed and random effects. You w, Sas .For Linear Models to the inventory that you are selling on WonderClubX
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Add Sas .For Linear Models, This clear and comprehensive guide provides everything you need for powerful linear model analysis. Using a tutorial approach and plenty of examples, the authors lead you through methods related to analysis of variance with fixed and random effects. You w, Sas .For Linear Models to your collection on WonderClub |
