Applied linear statistical models : regression, analysis of variance, and experimental designs / John Neter, William Wasserman and Michael H. Kutner.
By: Neter, John
.
Contributor(s): Wasserman, William | Kutner, Michael H.
Material type: 
BookPublisher: Homewood, IL : Irwin, 1990Edition: 3rd edition.Description: xvi, 1181 p. : ill. ; 25 cm.ISBN: 025608338X.Subject(s): Regression analysis | Analysis of variance | Experimental design | Linear models (Statistics)DDC classification: 519.536 | Item type | Current library | Call number | Copy number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|
| General Lending | MTU Bishopstown Library Lending | 519.536 (Browse shelf(Opens below)) | 1 | Available | 00191642 | ||
| General Lending | MTU Bishopstown Library Lending | 519.536 (Browse shelf(Opens below)) | 1 | Available | 00009592 |
Enhanced descriptions from Syndetics:
There are two approaches to undergraduate and graduate courses in linear statistical models and experimental design in applied statistics. One is a two-term sequence focusing on regression followed by ANOVA/Experimental design. Applied Linear Statistical Models serves that market. It is offered in business, economics, statistics, industrial engineering, public health, medicine, and psychology departments in four-year colleges and universities, and graduate schools. Applied Linear Statistical Models is the leading text in the market. It is noted for its quality and clarity, and its authorship is first-rate. The approach used in the text is an applied one, with an emphasis on understanding of concepts and exposition by means of examples. Sufficient theoretical foundations are provided so that applications of regression analysis can be carried out comfortably. The fourth edition has been updated to keep it current with important new developments in regression analysis.
"Free instructor's copy ... not for sale"--Cover..
Bibliography: (pages 1169-1173) and index.
Part I: Simple linear regression -- Part II: General linear regression -- Part III: Single factor analysis of variance -- Part IV: Multifactor analysis of variance -- Part V: Experimental designs.
Table of contents provided by Syndetics
- 1 Linear Regression with One Independent Variable
- 2 Inferences in Regression Analysis
- 3 Diagnostic and Remedial Measures
- 4 Simultaneous Inferences and Other Topics in Regression Analysis
- 5 Matrix Approach to Simple Linear Regression Analysis
- 6 Multiple Regression I
- 7 Multiple Regression II
- 8 Building the Regression Model I: Selection of Predictor Variables
- 9 Building the Regression Model II: Diagnostics
- 10 Building the Regression Model III: Remedial Measures and Validation
- 11 Qualitative Predictor Variables
- 12 Autocorrelation in Time Series Data
- 13 Introduction to Nonlinear Regression
- 14 Logistic Regression, Poisson Regression, and Generalized Linear Models
- 15 Normal Correlation Models
- 16 Analysis of Variance
- 17 Analysis of Factor-Level Effects
- 18 ANOVA Diagnostics and Remedial Measures
- 19 Two-Factor Analysis of VarianceßEqual Sample Sizes
- 20 Analysis of Factor Effects in Two-Factor StudiesßEqual Sample Sizes
- 21 Two-Factor StudiesßOne Case per Treatment
- 22 Two Factor StudiesßUnequal Sample Sizes and Unequal Treatment Importance
- 23 Multi-Factor Studies
- 24 Random and Mixed-Effect Models
- 25 Analysis of Covariance
- 26 Design of Experiments, Randomization, and Sample Size Planning
- 27 Randomized Block Designs
- 28 Nested Designs, Subsampling, and Partially Nested Designs
- 29 Repeated Measure Designs
- 30 Latin Square and Related Designs
- 31 Explanatory Experiments--Two-level Factorial and Fractional Factorial Designs
- 32 Response Surface Methodology
- Appendixes