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Discovering statistics using SPSS : (and sex, drugs and rock 'n' roll) / Andy Field

Main Author Field, Andy Country Reino Unido. Edition 2nd ed Publication London : Sage Publications, imp. 2006 Description XXXIV, 779 p. : il. ; 24 cm + 1 disco óptico (CD-ROM) Series ISM - introducing statistical methods ISBN 0-7619-4452-4
CDU 519.2 303.7:681.3.06 681.3.06:303.7
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Enhanced descriptions from Syndetics:

Quite simply the only book on statistics that students will need to buy at university. What's new in the Second Edition? 1. Fully compliant with the latest version of SPSS version 12 2. More coverage of advanced statistics including completely new coverage of non-parametric statistics. The book is 50 per cent longer than the First Edition. 3. Each section of each chapter now has a notation - 1,2 or 3 - referring to the intended level of study. This helps students navigate their way through the book and makes it user-friendly for students of ALL levels. 4. Has a 'how to use this book' section at the start of the text. 5. Characters in each chapter have defined roles - summarizing key points, to pose questions etc 6. Each chapter now has several examples for students to work through. Answers provided on the enclosed CD-ROM 7. Many more datasets than in the previous edition on the CD-ROM

Table of contents provided by Syndetics

  • Everything you Wanted to Know About Statistics (Well, Sort of)
  • Building Statistical Models
  • Populations and Samples
  • Simple Statistical Models
  • Frequency Distributions
  • Is My Sample Representative of the Population?
  • Linear Models
  • How Can We Tell If Our Model Represents the Real World?
  • The SPSS Environment
  • Versions of SPSS Getting Started
  • The Data Editor
  • The Output Viewer
  • The Syntax Window Saving Files Retrieving a File
  • Exploring Data
  • Parametric Data
  • Graphing and Screening Data
  • Exploring Groups of Data
  • Testing Whether a Distribution is Normal Testing for Homogeneity of Variance Graphing Means
  • Correlation
  • How Do We Measure Relationships?
  • Data Entry for Correlation Analysis
  • Using SPSS Graphing Relationships
  • The Scatterplot Bivariate Correlation
  • Partial Correlation
  • How To Report Correlation Coefficients
  • regression
  • An Introduction to Regression
  • Doing Simple Regression on SPSS
  • Interpreting a Simple Regression Multiple Regression
  • The Basics How Accurate Is My Regression Model?
  • How To Do Multiple Regression Using SPSS
  • Interpreting Multiple Regression
  • How To Report Multiple Regression Categorical Predictors and Multiple Regression
  • Logistic Regression
  • Background to Logistic Regression
  • What Are the Principles behind Logistic Regression?
  • Running the Analysis A Research Example Interpreting Logistic Regression
  • How To Report Logistic Regression Another Example
  • Testing for Multicollinearity Things That Can Go Wrong
  • Comparing Two Means
  • Revision of Experimental Research
  • Inputting Data and Displaying Means with Error Bar Charts
  • Testing Differences between Means
  • The t-Test
  • The Dependent t-Test
  • The Independent t-Test Between Groups or Repeated Measures?
  • The t-Test as a General Linear Model
  • What If Our Data Are Not Normally Distributed?
  • Comparing Several Means: Anova (GLM 1)
  • The Theory behind ANOVA
  • Running One-Way ANOVA on SPSS
  • Output from One-Way ANOVA
  • Calculating the Effect Size Reporting Results from One-Way Independent
  • ANOVA Violations of Assumptions in One-Way Independent
  • ANOVA Analysis of Covariance, ANCOVA (GLM 2)
  • What Is ANCOVA?
  • Conducting ANCOVA on SPSS Interpreting the Output from ANCOVA
  • ANCOVA Run as a Multiple Regression
  • Additional Assumptions in ANCOVA
  • Calculating the Effect Size Reporting Results
  • Factorial ANOVA (GLM 3)
  • Theory of Factorial ANOVA (Between Groups)
  • Factorial ANOVA Using SPSS Output from Factorial
  • ANOVA Interpreting Interaction Graphs
  • Calculating Effect Sizes Reporting the Results of Two-Way ANOVA
  • Factorial ANOVA as Regression
  • Repeated-Measures Designs (GLM 4)
  • Introduction to Repeated-Measures
  • Designs Theory of One-Way Repeated-Measures
  • ANOVA One-Way Repeated-Measures
  • ANOVA Using SPSS Output for One-Way Repeated-Measures
  • ANOVA Effect Sizes for Repeated-Measures
  • ANOVA Reporting One-Way Repeated-Measures
  • ANOVA Repeated-Measures with Several Independent Variables
  • Output for Factorial Repeated-Measures
  • ANOVA Effect Sizes for Factorial Repeated-Measures
  • ANOVA Reporting the Results from Factorial Repeated-Measures
  • ANOVA Mixed Design ANOVA (GLM 5)
  • Mixed ANOVA on SPSS Output for Mixed Factorial
  • ANOVA Main Analysis Calculating Effect Sizes
  • Reporting the Results of Mixed
  • ANOVA Non-Parametric Tests
  • Comparing Two Independent Conditions
  • The Wilcoxon Rank-Sum
  • Test and Mann-Whitney
  • Test Comparing Two Related Conditions
  • The Wilcoxon Signed-Rank
  • Test Differences between Several Independent Groups
  • The Kruskal-Wallis Test
  • Differences between Several Related Groups Friedman's
  • ANOVA Multivariate Analysis of Variance (MANOVA)
  • Introduction Similarities and Differences to ANOVA
  • Theory of MANOVA Assumptions of MANOVA
  • MANOVA on SPSS Output from MANOVA Following Up MANOVA wi

Reviews provided by Syndetics


This new edition (1st ed., 2000) offers new material, including additional examples, how to report the analysis, how to calculate effect sizes, a glossary of key terms, boxed summaries of the main points highlighting interesting issues, new chapters on nonparametric statistics, analysis of categorical data, and a new section of reliability analysis. It presents difficult and complex statistical concepts and techniques in a lively, reader-friendly style. Field makes concerted efforts to provide statistical tools in a very lighthearted fashion by throwing in humor, with great success. Of software available, Field prefers SPSS to carry out data analysis. Chapters describe basic statistical terms; the SPSS environment; exploring data, correlation coefficients of different kinds, regression, and logistic regression; comparing means of two populations, analysis of variance, and analysis of covariance; and factorial experiments, repeated measure designs, mixed designs, nonparametric test, multivariate analysis of variance, factor analysis, and analysis of categorical data. For support it is suggested that readers consult , , and a CD-ROM accompanying the latter. Each section is coded with an icon designed to reflect the difficulty of the material therein. There is an appendix with statistical tables and a useful index. Very useful, valuable, and interesting. ^BSumming Up: Highly recommended. Lower-division undergraduates through graduate students; professionals. D. V. Chopra Wichita State University

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