Skip to content

Applied Linear Statistical Models

Spend $50 to get a free movie!

ISBN-10: 007310874X

ISBN-13: 9780073108742

Edition: 5th 2005

Authors: Michael H. Kutner, Christopher J. Nachtsheim, John Neter, William Li, Jackie L. Butler

List price: $230.00
Blue ribbon 30 day, 100% satisfaction guarantee!
what's this?
Rush Rewards U
Members Receive:
Carrot Coin icon
XP icon
You have reached 400 XP and carrot coins. That is the daily max!


Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples…    
Customers also bought

Book details

List price: $230.00
Edition: 5th
Copyright year: 2005
Publisher: McGraw-Hill Higher Education
Publication date: 8/10/2004
Binding: Mixed Media
Size: 7.50" wide x 9.25" long x 2.00" tall
Weight: 4.840
Language: English

Simple Linear Regression
Linear Regression with One Predictor Variable
Inferences in Regression and Correlation Analysis
Diagnostics and Remedial Measures
Simultaneous Inferences and Other Topics in Regression Analysis
Matrix Approach to Simple Linear Regression Analysis
Multiple Linear Regression
Multiple Regression I
Multiple Regression II
Regression Models for Quantitative and Qualitative Predictors
Building the Regression Model I: Model Selection and Validation
Building the Regression Model II: Diagnostics
Building the Regression Model III: Remedial Measures
Autocorrelation in Time Series Data
NonLinear Regression
Introduction to Nonlinear Regression and Neural Networks
Logistic Regression, Poisson Regression, and Generalized Linear Models
Design and Analysis of Single-Factor Studies
Introduction to the Design of Experimental and Observational Studies
Single-Factor Studies
Analysis of Factor Level Means
ANOVA Diagnostics and Remedial Measures
Multi-Factor Studies
Two-Factor Studies with Equal Sample Sizes
Two-Factor Studies-One Case per Treatment
Randomized Complete Block Designs
Analysis of Covariance
Two-Factor Studies with Unequal Sample Sizes
Multifactor Studies
Random and Mixed Effects Models
Specialized Study Designs
Nested Designs, Subsampling, and Partially Nested Designs
Repeated Measures and Related Designs
Balanced Incomplete Block, Latin Square, and Related Designs
Exploratory Experiments: Two-Level Factorial and Fractional Factorial Designs
Response Surface Methodology
Some Basic Results in Probability and Statistics
Data Sets
Rules for Developing ANOVA Models and Tables for Balanced Designs
Selected Bibliography