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" Applied linear regression models "
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BL
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| Record Number
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621915
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| Doc. No
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dltt
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| Main Entry
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Kutner, Michael H
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| Title & Author
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Applied linear regression models
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| Edition Statement
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Fourth edition // Michael H. Kutner, Christopher J. Nachtsheim, John Neter
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| Series Statement
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The McGraw-Hill/Irwin series: operations and decision sciences
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| Page. NO
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xvii, 701 pages :: illustrations ;; 24 cm ++ 1 CD-ROM (4 3/4 in.)
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| ISBN
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0072386916
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: 9780072386912
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: 9780073014661
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: 0073014664
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: 9780073013442
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: 0073013447
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: 0071232524
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: 9780071232524
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| Bibliographies/Indexes
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Includes bibliographical references (pages 687-693) and index
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| Contents
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pt. I. 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 -- pt. II. 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 -- pt. III. Nonlinear regression. Introduction to nonlinear regression and neural networks -- Logistic regression, Poisson regression, and generalized linear models
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| Subject
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Regression analysis
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| Subject
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Regresyon analizi
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| Subject
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Linear Models
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| Dewey Classification
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519.5/36
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| LC Classification
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QA278.2.N46 2004
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| NLM classification
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QA278.2K975a 2004
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| Added Entry
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Nachtsheim, Chris
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Neter, John
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