The book 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 giv
Linear Regression Analysis, Second Edition
β Scribed by George A. F. Seber, Alan J. Lee(auth.)
- Year
- 2003
- Tongue
- English
- Leaves
- 572
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Concise, mathematically clear, and comprehensive treatment of the subject.
* Expanded coverage of diagnostics and methods of model fitting.
* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.
* More than 200 problems throughout the book plus outline solutions for the exercises.
* This revision has been extensively class-tested.Content:
Chapter 1 Vectors of Random Variables (pages 1β16):
Chapter 2 Multivariate Normal Distribution (pages 17β33):
Chapter 3 Linear Regression: Estimation and Distribution Theory (pages 35β95):
Chapter 4 Hypothesis Testing (pages 97β118):
Chapter 5 Confidence Intervals and Regions (pages 119β137):
Chapter 6 Straight?Line Regression (pages 139β163):
Chapter 7 Polynomial Regression (pages 165β185):
Chapter 8 Analysis of Variance (pages 187β226):
Chapter 9 Departures from Underlying Assumptions (pages 227β263):
Chapter 10 Departures from Assumptions: Diagnosis and Remedies (pages 265β328):
Chapter 11 Computational Algorithms for Fitting a Regression (pages 329β389):
Chapter 12 Prediction and Model Selection (pages 391β456):
β¦ Subjects
ΠΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠ°;Π’Π΅ΠΎΡΠΈΡ Π²Π΅ΡΠΎΡΡΠ½ΠΎΡΡΠ΅ΠΉ ΠΈ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ°;ΠΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠ°;
π SIMILAR VOLUMES
Now revised and updated, this brisk introduction to functional analysis is intended for advanced undergraduate students, typically final year, who have had some background in real analysis. The author's aim is not just to cover the standard material in a standard way, but to present results of appli
Concise, mathematically clear, and comprehensive treatment of the subject.* Expanded coverage of diagnostics and methods of model fitting.* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance mode
Concise, mathematically clear, and comprehensive treatment of the subject.<br>* Expanded coverage of diagnostics and methods of model fitting.<br>* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of varia
Treats linear regression diagnostics as a tool for application of linear regression models to real-life data. Presentation makes extensive use of examples to illustrate theory. Assesses the effect of measurement errors on the estimated coefficients, which is not accounted for in a standard least squ