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      1. Naturvetenskap och teknik
      2. Matematik och naturvetenskap
      3. Matematik
      4. Matematisk statistik

      Data Analysis with SPSS

      A First Course in Applied Statistics

      AvStephen Sweet,Karen Grace-Martin

      Häftad, Engelska, 2011

      1 555 kr

      Beställningsvara. Skickas inom 7-10 vardagar. Fri frakt över 249 kr.

      Beskrivning

      Data Analysis with SPSS is designed to teach students how to explore data in a systematic manner using the most popular professional social statistics program on the market today.

       

      Written in ten manageable chapters, this book first introduces students to the approach researchers use to frame research questions and the logic of establishing causal relations. Students are then oriented to the SPSS program and how to examine data sets. Subsequent chapters guide them through univariate analysis, bivariate analysis, graphic analysis, and multivariate analysis. Students conclude their course by learning how to write a research report and by engaging in their own research project.

       

      Each book is packaged with a disk containing the GSS (General Social Survey) file and the States data files. The GSS file contains 100 variables generated from interviews with 2,900 people, concerning their behaviors and attitudes on a wide variety of issues such as abortion, religion, prejudice, sexuality, and politics. The States data allows comparison of all 50 states with 400 variables indicating issues such as unemployment, environment, criminality, population, and education. Students will ultimately use these data to conduct their own independent research project with SPSS.

       

      Note: MySearchLab does not come automatically packaged with this text. To purchase MySearchLab, please visit: www.mysearchlab.com or you can purchase a ValuePack of the text + MySearchLab with Pearson eText (at no additional cost). ValuePack ISBN-10: 0205863728 / ValuePack ISBN-13: 9780205863723

      Produktinformation

      • Utgivningsdatum:2011-05-05
      • Mått:215 x 276 x 15 mm
      • Vikt:680 g
      • Format:Häftad
      • Språk:Engelska
      • Antal sidor:288
      • Upplaga:4
      • Förlag:Pearson Education
      • ISBN:9780205019670

      Utforska kategorier

      • Matematisk statistik inom Naturvetenskap och teknik

      Innehållsförteckning

      • TABLE OF CONTENTS:1. BRIEF2. COMPREHENSIVE  BRIEF TABLE OF CONTENTS  Chapter 1  •   Key Concepts in Social Science Research        Chapter 2  •   Getting Started: Accessing, Examining, and Saving  Chapter 3   •  Univariate Analysis: Descriptive Statistics         Chapter 4   • Constructing Variables      Chapter 5   •  Assessing Association through Bivariate Analysis           Chapter 6   •  Comparing Group Means through Bivariate Analysis             Chapter 7   •  Modeling Relationships of Multiple Variables with Linear Regression                                 Chapter 8   •  Logistic Regression         Chapter 9   •  Writing a Research Report          Chapter 10 •  Research Projects                                                  COMPREHENSIVE TABLE OF CONTENTS   Chapter 1  • Key Concepts in Social Science Research       Overview          Framing Topics Into Research Questions            Theories and Hypotheses            Population and Samples                         Relationships and Causality        Data Sets                                       Parts of a Data Set                        Reliability and Validity                 Summary          Key Terms        Exercises              Chapter 2 •  Getting Started: Accessing, Examining, and Saving Data                       Overview                 The Layout of SPSS      Types of Variables        Initial Settings                           Defining and Saving a New Data Set                 Managing Data Sets: Dropping and Adding Variables, Merging Data Sets Dropping and Adding Variables                         Merging and Importing Files                                   Loading and Examining an Existing File      Summary          Key Terms             Exercises              Chapter 3  •  Univariate Analysis: Descriptive Statistics         Overview           Why Do Researchers Perform Univariate Analysis?                    Exploring Distributions of Scale Variables                                       Exploring Distributions of Categorical Variables                Summary          Key Terms       Exercises            Chapter 4  • Constructing Variables      Overview          Why Construct New Variables From Existing Data?       Recoding Existing Variables                   Computing New Variables                     Recording Computations Using Syntax    Minimizing Missing Values in Computing New Variables        Summary         Key Terms       Exercises           Chapter 5  •  Assessing Association through Bivariate Analysis           Overview          Why Do We Need Significance Tests?            Analyzing Bivariate Relationships Between Two Categorical Variables    Analyzing Bivariate Relationships Between Two Scale Variables             Summary             Key Terms       Exercises           Chapter 6  •  Comparing Group Means through Bivariate Analysis             Overview             One-Way Analysis of Variance     Post-hoc Tests                             Assumptions of ANOVA              Graphing the Results of ANOVA           T tests               Summary          Key Terms      Exercises           Chapter 7  •  Modeling Relationships of Multiple Variables with Linear Regression                          Overview           The Advantages of Modeling Relationships in Multiple Regression            Linear Regression: A Bivariate Example                                       Multiple Linear Regression         Other Concerns In Applying Linear Regression     Building Multiple Variable Models         Summary               Key Terms        Exercises               Chapter 8  •  Logistic Regression         Overview             What Is Logistic Regression?                 When Can I Use a Logistic Regression?              Understanding  Relationships through Probabilities           Logistic Regression: A Bivariate Example                          Multiple Variable Logistic Regression: An Example            Summary              Key Terms           Exercises             Chapter 9  •  Writing a Research Report          Overview          Writing Style and Audience                       The Structure of a Report                         Summary              Key Terms            Exercises                      Chapter 10  •  Research Projects                       Potential Research Projects                       Research Project 1: Racism                       Research Project 2: Suicide                        Research Project 3: Criminality                  Research Project 4: Welfare and Other Public Aid Consumption                  Research Project 5: Sexual Behavior          Research Project 6: Education                  Research Project 7: Health                    Research Project 8: Happiness               Research Project 9: Your Topic
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