Applied Linear Statistical Models (4th International edition)

Applied Linear Statistical Models (4th International edition)

By: Michael H. Kutner (author), John Neter (author), Christopher J. Nachtsheim (author), William Wasserman (author)Paperback

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"Applied Linear Statistical Models", 5e, 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 "Notes" to provide depth and statistical accuracy and precision. 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 methods can be automated within software without loss of understanding, it is so done.

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Part1 Simple Linear Regression 1 Linear Regression with One Predictor Variable 2 Inferences in Regression 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 Single Factor Studies 15 Introduction to the Design of Experiments 16 Analysis of Single-Factor Studies 17 Analysis of Factor Level Effects in Single Factor Studies 18 ANOVA Diagnostics and Remedial Measures Part 5 Two -Factor Studies and Blocking 19 Two -Factor Studies- Equal Sample Sizes 20 Two -Factor Studies-One Case per Cell 21 Randomized Complete Block Designs and the Analysis of Covariance 22 Two -Factor Studies-Unequal Sample Sizes and Unequal Treatment Importance Part 6 Multifactor Studies 23 Multifactor Studies 24 Random and Mixed-Effects Models 25 Nested Designs, Subsampling, and Partially Nested Designs 26 Repeated Measures and Related Designs 27 Latin Square, Balanced Incomplete Block, and Related Designs 28 Exploratory Experiments-Two-Level Factorial and Fractional Factorial Designs 29 Response Surface Experiments

Product Details

  • publication date: 01/11/2004
  • ISBN13: 9780071122214
  • Format: Paperback
  • Number Of Pages: 1396
  • ID: 9780071122214
  • weight: 2137
  • ISBN10: 0071122214
  • edition: 4th International edition

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