Data Analysis

  • Data Analysis: An Introduction
    Data Analysis: An Introduction
    By Michael Lewis-Beck

    "Written at a level appropriate for the advanced undergraduate course on data analysis, this accessible volume introduces the reader to the "art" of data analysis from data-gathering to multiple regression in which a dependent variable is ...

  • Data Analysis: An Introduction
    Data Analysis: An Introduction
    By Michael Lewis-Beck

    REFERENCES ALDRICH, J., and NELSON, F. (1984) Linear Probability, Logit, and Probit Models. Sage University Paper series on Quantitative Applications in the ... BERRY, W. D., and FELDMAN, S. (1985). Multiple Regression in Practice.

  • Data Analysis: A Statistical Primer for Psychology Students
    Data Analysis: A Statistical Primer for Psychology Students
    By Edward L. Wike

    A Statistical Primer for Psychology Students Edward L. Wike ... Regarding the detection of errors, Underwood says : To determine whether or not there is an error in an investigation requires a comparison of what the investigator does ...

  • Data Analysis: A Model Comparison Approach To Regression, ANOVA, and Beyond, Third Edition
    Data Analysis: A Model Comparison Approach To Regression, ANOVA, and Beyond, Third Edition
    By Carey S. Ryan, Charles M. Judd, Gary H. McClelland

    Highlights of the third edition include: a new chapter on logistic regression; expanded treatment of mixed models for data with multiple random factors; updated examples; an enhanced website with PowerPoint presentations and other tools ...

  • Data Analysis: Intermediate
    By Margaret Thomas

    Data Analysis: Intermediate

  • Data Analysis
    By Margaret Thomas, National Council of Teachers of Mathematics, School Specialty Publishing

    Data Analysis

  • Data Analysis: What Can Be Learned From the Past 50 Years
    Data Analysis: What Can Be Learned From the Past 50 Years
    By Peter J. Huber

    This book explores the many provocative questions concerning the fundamentals of data analysis. It is based on the time-tested experience of one of the gurus of the subject matter. Why should one study data analysis?

  • Data Analysis: A Bayesian Tutorial
    Data Analysis: A Bayesian Tutorial
    By John Skilling, Devinderjit Sivia

    One of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples. - Katie St. Clair MAA Reviews.

  • Data Analysis: A Model Comparison Approach To Regression, ANOVA, and Beyond, Third Edition
    Data Analysis: A Model Comparison Approach To Regression, ANOVA, and Beyond, Third Edition
    By Carey S. Ryan, Charles M. Judd, Gary H. McClelland

    Highlights of the third edition include: a new chapter on logistic regression; expanded treatment of mixed models for data with multiple random factors; updated examples; an enhanced website with PowerPoint presentations and other tools ...

  • Data Analysis
    By Gary McClelland

    Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis.

  • Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond
    Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond
    By Carey S. Ryan, Charles M. Judd, Gary H. McClelland

    Noted for its model-comparison approach and unified framework based on the general linear model (GLM), this classic text provides readers with a greater understanding of a variety of statistical procedures including analysis of variance ...

  • Data Analysis: A Model Comparison Approach, Second Edition
    Data Analysis: A Model Comparison Approach, Second Edition
    By Carey S. Ryan, Charles M. Judd, Gary H. McClelland

    The book opens with an overview of data analysis. All the necessary concepts for statistical inference used throughout the book are introduced in Chapters 2 through 4. The remainder of the book builds on these models.

  • Data Analysis: Statistical and Computational Methods for Scientists and Engineers
    Data Analysis: Statistical and Computational Methods for Scientists and Engineers
    By Siegmund Brandt

    It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The book is conceived both as an introduction and as a work of reference.

  • Data Analysis: A Statistical Primer for Psychology Students
    Data Analysis: A Statistical Primer for Psychology Students
    By Edward L. Wike

    This book is intended for psychology majors and graduate students who are conducting experiments for the first time and are faced with the task of making sense out of their data.

  • Data Analysis: Scientific Modeling and Practical Application
    Data Analysis: Scientific Modeling and Practical Application
    By Martin Schader, Wolfgang A. Gaul, Otto Opitz

    ... Forecasting Economic Time Series . Cambridge University Press , Cambridge . FOX , A.J. ( 1972 ) : Outliers in Time Series . J ... Robustness of statistical forecasting . Ab- stracts of 4 - th World Congress of the Bernoulli Society , 265 ...

  • Data Analysis: Statistical and Computational Methods for Scientists and Engineers
    Data Analysis: Statistical and Computational Methods for Scientists and Engineers
    By Siegmund Brandt

    Bridging the gap between statistical theory and physical experiment, this is a thorough introduction to the statistical methods used in the experimental physical sciences and to the numerical methods used to implement them.