Applied Linear Statistical Models – Michael Kutner – 5th Edition


Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling, analysis of variance, and the design of experiments. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work.

The text proceeds through linear and nonlinear 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 precision.

Applications used within the text and the hallmark problems, exercises, projects, and case studies 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 the use of automated software without loss of understanding.

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  • Part 1 Simple Linear Regression
    1 Linear Regression with One Predictor Variable
    2 Inferences in Regression and Correlation Analysis
    3 Diagnostic 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
    29Exploratory 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 Develping ANOVA Models and Tables for Balanced Designs
    Appendix E: Selected Bibliography
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