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Data analysis with SPSS : a first course in applied statistics

Autor: Stephen A Sweet; Karen Grace-Martin
Editora: Boston, Mass. ; London : Allyn and Bacon, ©2008.
Edição/Formato   Livro : Inglês : 3rd edVer todas as edições e formatos
Base de Dados:WorldCat
Resumo:

This text is designed to teach students how to explore data in a systematic manner using one of the most popular professional social statistics programmes.

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Detalhes

Tipo de Documento: Livro
Todos os Autores / Contribuintes: Stephen A Sweet; Karen Grace-Martin
ISBN: 9780205483877 0205483879
Número OCLC: 213106438
Notas: Previous edition: 2002.
Includes CD-ROM.
Descrição: xi, 273 pages : illustrations ; 28 cm + 1 CD-ROM
Conteúdos: Brief Table of Contents: Chapter 1: Key Concepts in Social Science Research Chapter 2: Getting Started: Accessing, Examining, and Saving Data Chapter 3: Univariate Analysis: Descriptive Statistics Chapter 4: Constructing Variables Chapter 5: Assessing Association through Bivariate Analysis Chapter 6: Comparing Groups through Bivariate Analysis Chapter 7: Multivariate Analysis with Linear Regression Chapter 8 Multivariate Analysis with Logistic Regression Chapter 9: Writing a Research Report Chapter 10: Research Projects Comprehensive Table of Contents: *Each chapter begins with "Overview," and concludes with "Summary," "Key Terms", and "Exercises." Chapter1: Key Concepts in Social Science Research Why Do We Need Statistics Framing Topics Into Research Questions Theory and Hypothesis Population and Samples Relationships and Causality Data Chapter 2: Getting Started: Accessing, Examining,and Saving Data Initial Settings The Layout of SPSS Types of Variables Defining and Saving a New Data Set Managing Data Sets: Dropping and Adding Variables Merging and Importing Files Loading and Examining an Existing File Chapter 3: Univariate Analysis: Descriptive Statistics Why Do Researchers Perform Univariate Analysis? Exploring Distributions of Scale Variables Exploring Distributions of Categorical Variables Chapter 4: Constructing Variables Why Construct New Variables? Recoding Existing Variables Computing New Variables Recording Computations Using Syntax Chapter 5: Assessing Association through Bivariate Analysis Why Do We Need Significance Tests? Cross Tabulations Bar Charts Correlations Scatter Plots Chapter 6: Comparing Groups through Bivariate Analysis One-Way Analysis of Variance Post-hoc Tests Assumptions of ANOVA Graphing the Results of ANOVA T tests Chapter 7: Multivariate Analysis with Linear Regression The Advantages of Multivariate Analysis Linear Regression: A Bivariate Example Multiple Linear Regression Other Concerns In Applying Linear Regression Assumptions of Regression Dummy Variables Outliers Causality Chapter 8: Multivariate Analysis with Logistic Regression What Is Logistic Regression? When Can I Do a Logistic Regression? Understanding the Relationships through Probabilities Logistic Regression: A Bivariate Example Multivariate Logistic Regression: An Example Interpreting Logistic Regression Output Using Multivariate Logistic Regression Coefficients to Make Predictions Using Multivariate Coefficients to Graph a Logistic Regression Line Chapter 9: Writing a Research Report Overview Writing Style and Audience The Structure of a Report References and Further Reading Chapter 10: Research Projects Potential Research Projects Research Project 1: Racism Research Project 2: Suicide Research Project 3: Criminality Research Project 4: Welfare Research Project 5: Sexual Behavior Research Project 6: Education Research Project 7: Health Research Project 8: Happiness Research Project 9: Your Topic Appendix 1: STATES.SAV Descriptives Appendix 2: GSS98.SAV File Information Appendix 3: Variable Label Abbreviations Permissions Index
Responsabilidade: Stephen A. Sweet, Karen Grace-Martin.

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