Author Michael Kutner
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Applied Linear Statistical Models / Michael Kutner / McGraw-Hill/Irwin (2004)
Applied Linear Statistical Models [printed text] / Michael Kutner, Author ; William Li ; John Neter ; Christopher Nachtsheim, Author . - 5th ed. . - [S.l.] : McGraw-Hill/Irwin, 2004 . - xxviii, 1396 p. : ill. ; 24 cm. + 1 CD-ROM (4 3/4 in.).
ISBN : 978-0-07-238688-2 : 63,49
System requirements for accompanying CD-ROM: PC, pentium based processor; Microsoft Windows 98/2000/XP; IE explorer 5.5; MS Office or equivalent.
Includes bibliographical references (p. 1374-1384) and index.
Languages : French (fre)
QA 278.2 Regression Analysis (Mathematical Statistics / Multivariate Analysis) - HA29 Theory and method of social science statistics (General works/ English)
Analysis of Variance ; Experimental design ; Linear Models ; Regression analysis ; Textbooks
Abstract: Applied Linear Statistical Models is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. 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 "Comments" to provide depth and statistical accuracy and completeness. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. 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 and exercises, and where possible integrates methods with commercially-available statistical software. Contents note: Part1 Simple Linear Regression -- 1 Linear Regression with One Predictor Variable -- 2 Inferences in Regression and Correlation Analysis -- 3 Diagnostics and Remedial Measures -- 4 Simultaneous Inferences and Other Topics in Regression Analysis -- 5 Matrix Approach to Simple Linear Regression Analysis -- Part 2 Multiple Linear Regression -- 6 Multiple Regression I -- 7 Multiple Regression II -- 8 Regression Models for Quantitative and Qualitative Predictors -- 9 Building the Regression Model I: Model Selection and Validation -- 10 Building the Regression Model II: Diagnostics -- 11 Building the Regression Model III: Remedial Measures -- 12 Autocorrelation in Time Series Data -- Part 3 NonLinear Regression -- 13 Introduction to Nonlinear Regression and Neural Networks -- 14 Logistic Regression, Poisson Regression, and Generalized Linear Models -- Part 4 Design and Analysis of Single-Factor Studies -- 15 Introduction to the Design of Experimental and Observational Studies -- 16 Single-Factor Studies -- 17 Analysis of Factor Level Means -- 18 ANOVA Diagnostics and Remedial Measures -- Part 5 Multi-Factor Studies -- 19 Two-Factor Studies with Equal Sample Sizes -- 20 Two-Factor Studies-One Case per Treatment -- 21 Randomized Complete Block Designs -- 22 Analysis of Covariance -- 23 Two-Factor Studies with Unequal Sample Sizes -- 24 Multifactor Studies -- 25 Random and Mixed Effects Models -- Part 6 Specialized Study Designs -- 26 Nested Designs, Subsampling, and Partially Nested Designs -- 27 Repeated Measures and Related Designs -- 28 Balanced Incomplete Block, Latin Square, and Related Designs -- 29 Exploratory Experiments: Two-Level Factorial and Fractional Factorial Designs -- 30 Response Surface Methodology -- Appendix A: Some Basic Results in Probability and Statistics -- Appendix B: Tables -- Appendix C: Data Sets -- Appendix D: Rules for Developing ANOVA Models and Tables for Balanced Designs -- Appendix E: Selected Bibliography Record link:
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Barcode Call number Media type Location Section Status 10273-01047 QA 278.2/KUT Book KCE Library (10.124) Due for return by 12/31/2020
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