Statistical Methods for Practice and Research: a Guide to Data Analysis Using SPSS

1. Introduction to SPSS 15
1.1 Starting SPSS 15
1.2 SPSS Main Menus 16
1.3 Working with the Data Editor 18
1.4 SPSS Viewer 22
1.5 Importing and Exporting Data 24
2. Basic Statistical Concepts 28
2.1 Research in Behavioral Sciences 28
2.1.1 Qualitative Research 28
2.1.2 Quantitative Research 29
2.2 Types of Variables 30
2.2.1 Qualitative Variables 30
2.2.2 Quantitative Variables * 31
2.3 Reliability and Validity 31
2.3.1 Assessing Reliability 32
2.3.2 Assessing Validity ' 32
2.4 Hypothesis Testing 33
2.4.1 Type I and Type 11 Errors 35
2.4.2 Significance Level (p-value) 35
2.4.3 One-Tailed and Two-Tailed Tests 35
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3. Summarizing Data: Descriptive Statistics 37
3.1 Basic Concepts 37
3.1.1 Measures of Central Tendency 38
3.1.2 Measures of Variability 38
3.1.3 Percentiles, QuartUes, and Interquartile Range 39
3.1.4 Skewness 39
3.1.5 Kurtosis 40
3.2 Using SPSS 40
3.2.1 Descriptive Statistics 41
3.2.2 Frequencies 44
3.2.3 Tables 49
4. Comparing Means: One or Two Samples t-Tests 52
4.1 Basic Concepts 52
4.1.1 Mest and z-test 52
4.1.2 One Sample f-test 53
4.1.3 Independent Samples Mest 53
4.1.4 Dependent (Paired) Samples Mest 54
4.2 Using SPSS 54
4.2.1 One Sample Mest 54
4.2.2 Independent Samples Mest 58
4.2.3 Dependent Samples Mest 63
5. Comparing Means: Analysis of Variance 67
5.1 Basic Concepts
5.1.1 ANOVA Procedure 67
5.1.2 Factors and Covariates 68
5.1.3 Between, Within, and Mixed (Between-Wlthin) Designs 69
5.1.4 Main Effects and Interactions 69
5.1.5 Post-Hoc Multiple Comparisons 70
5.1.6 Contrast Analysis
5.2 Using SPSS ^
5.2.1 One-Way Between-Groups ANOVA 71
5.2.2 Unplanned and Planned Comparisons 78
5.2.3 Two-Way Between-Groups ANOVA 55
6. Chi-Square Test of Independence for Discrete Data 91
6.1 Basic Concepts
6.1.1 Chi-Square Test of Independence
6.1.2 Contingency Tables
6.2 Using SPSS
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7. Correlation Analysis 99
7.1 Basic Concepts 99
7.1.1 Correlation Coefficient 99
7.1.2 Nature of Variables 100
7.1.3 Bivariate/Partial Correlation 100
7.2 Using SPSS 101
7.2.1 Bivariate Correlation 103
7.2.2 Partial Correlation 105
8. Multiple Regression 108
8.1 Basic Concepts 108
8.1.1 Regression Coefficient 108
8.1.2 Rvalues 109
8.1.3 Design Issues 109
8.1.4 Multiple Regression Types 110
8.2 Using SPSS 110
8.2.1 Standard Multiple Regression 111
8.2.2 Hierarchical Regression 117
9. Logistic Regression 171
9.1 Basic Concepts 121
9.1.1 Logistic Regression Coefficients ^ 121
9.1.2 Fit Indices 122
9.1.3 Design Issues 122
9.1.4 Logistic Regression Types 122
9.2 Using SPSS 123
10. Data Reduction and Scale Reliability: Factor Analysis 131
10.1 Basic Concepts ^ 131
10.1.1 Factor and Component 131
10.1.2 Exploratory and Confirmatoi^ Factor Analysis 132
10.1.3 Extraction 132
10.1.4 Factor Loadings 132
10.1.5 Rotation 133
10.1.6 Commimalities 133
10.1.7 Eigenvalue and Scree Plot 133
10.1.8 Scale Reliability 134
10.1.9 Sample Size Considerations 134
10.2 Using SPSS
10.2.1 Factor Analysis 134
10.2.2 Scale Reliability 145
11. Advanced Data Handling In SPSS 152
11.1 Sorting Cases
11.2 Merging Files
11.3 Aggregating Cases
11.4 Splitting Files
11.5 Selecting Cases
11.6 Recoding Values
11.7 Computing New Variables