社会统计学：应用MicroCase软件的课本【2025|PDF下载-Epub版本|mobi电子书|kindle百度云盘下载】

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Part Ⅰ Introduction and Univariate Analyses1

Chapter 1 Statistics and Variables3

1.1 Statistics and Data4

1.2 Overview of Statistics5

1.3 Samples and Populations6

1.4 Variables8

1.5 Levels of Measurement9

1.6 Mutually Exclusive and Collectively Exhaustive14

1.7 Continuous and Discrete Variables15

1.8 What Cases, Variables, and Data Files Look Like16

1.9 Aggregate Data18

1.10 Ideas and Thinking20

1.11 Playing with Data22

1.12 Summing Up Chapter 122

Chapter 2 Frequency and Percentage Distributions27

2.1 Frequency Distributions28

2.2 Percentage Distributions31

2.3 Cumulative Distributions34

2.4 Creating Sensible and Well-Formatted Tables36

2.5 Collapsing Variables38

2.6 Excluding Missing Data42

2.7 Selecting Subsets of Cases45

2.8 Pie Charts and Bar Graphs45

2.9 Outliers48

2.10 Mapping Ecological Variables49

2.11 Summing Up Chapter 251

Writing Statistics 1: Percentages Distributions, Graphs, and Maps55

Chapter 3 Averages61

3.1 Mode62

3.2 Median63

3.3 Mean66

3.4 Properties of the Mean68

3.5 The Mean for Dichotomous Variables70

3.6 Which to Use—Mode, Median, or Mean?72

3.7 Summing Up Chapter 375

Chapter 4 Measures of Variation79

4.1 Variances and Standard Deviations80

4.2 Shapes of Distributions87

4.3 Standard Scores (Z-Scores)89

4.4 Normal Distributions91

4.5 Sampling Distributions94

4.6 Confidence Intervals98

4.7 Some Cautions Using Univariate Statistics100

4.8 Summing Up Chapter 4102

Writing Statistics 2: Averages and Standard Deviations105

Part Ⅱ Bivariate Analyses107

Chapter 5 Cross-tabulation109

5.1 Bivariate Frequency Tables110

5.2 Bivariate Percentage Tables113

5.3 How to Read Percentage Tables116

5.4 Positive, Negative, and Curvilinear Relationships118

5.5 Format Conventions for Bivariate Tables122

5.6 Stacked Bar Graphs for Bivariate Relationships125

5.7 A Caution About Bivariate Tables Based on Small Ns126

5.8 Association Does Not Imply Causation127

5.9 Summing Up Chapter 5129

Chapter 6 The Chi-Square Test of Statistical Significance133

6.1 The Logic of Tests of Statistical Significance134

6.2 The Chi-Square Test137

6.3 Problems with Expected Frequencies Less Than 5144

6.4 Statistical Significance Does Not Mean Substantive Significance145

6.5 Significance Tests on Population Data147

6.6 Summing Up Chapter 6147

Chapter 7 Measures of Association for Cross-tabulations151

7.1 Overview of Measures of Association152

7.2 Chi-Square-Based Measures for Nominal Variables V and φ152

7.3 Lambda155

7.4 Choosing a Nominal Measure of Association158

7.5 Measures of Association for Ordinal Variables: Gamma159

7.6 Somers' DYX164

7.7 Measures of Association: An Overview168

7.8 Summing Up Chapter 7169

Writing Statistics 3: Bivariate Cross-tabulations172

Chapter 8 Comparison of Means and t Test175

8.1 Box-and-Whiskers Diagrams/Differences Between Means176

8.2 t Test for the Difference Between Means179

8.3 Assumptions and Cautions Concerning t Test186

8.4 One-Tailed and Two-Tailed Tests188

8.5 Confidence Intervals for Differences Between Means190

8.6 Summing Up Chapter 8192

Writing Statistics 4: Comparison of Means and t Test195

Chapter 9 Analysis of Variance197

9.1 Box-and-Whiskers Diagrams/Differences Among Means198

9.2 Purpose and Assumptions of Analysis of Variance201

9.3 The Logic of Analysis of Variance202

9.4 The ANOVA Table211

9.5 The Correlation Ratio (E2)211

9.6 Two-Way Analysis of Variance (and Beyond)213

9.7 Three Cautions About Statistically Significant F Ratios214

9.8 Summing Up Chapter 9215

Writing Statistics 5: Analysis of Variance218

Chapter 10 Regression and Correlation221

10.1 Scatterplots222

10.2 Scatterplots and the Strength of Relationships225

10.3 Some Limitations of Scatterplots228

10.4 Regression and Least-Squares Lines229

10.5 Calculating Regression Coefficients233

10.6 Correlation Coefficient (r)234

10.7 r2 as Proportion of Variation Explamed239

10.8 Correlations Between Dichotomous Variables241

10.9 Association Still Does Not Imply Causation242

10.10 Linear and Nonlinear Relationships242

10.11 Test of Significance for a Correlation Coefficient243

10.12 Correlation Matrix245

10.13 Summing Up Chapter 10247

Writing Statistics 6: Regression and Correlation251

Part Ⅲ Multivariate Analyses253

Chapter 11 Multivariate Cross-tabulation255

11.1 The Logic of Causal Relationships256

11.2 Spurious Relationships258

11.3 Some Terminology261

11.4 Examples of Spurious Relationships262

11.5 Replication263

11.6 Somewhere Between Explanation and Replication264

11.7 Specification265

11.8 Suppressor Variables266

11.9 Controlling for an Intervening Variable269

11.10 Partial Gamma271

11.11 An Overview of Elaboration272

11.12 Elaboration and Problems of Small Ns273

11.13 The Relationship of Multivariate Analysis to Experiment Design274

11.14 Summing Up Chapter 11276

Writing Statistics 7: Multivariate Cross-tabulation279

Chapter 12 Multiple Regression and Correlation281

12.1 Extending the Regression Model281

12.2 Multiple Correlation Coefficient287

12.3 Standardized Regression Coefficients (Beta Coefficients)289

12.4 Significance Tests for Multiple Correlation Coefficients291

12.5 Regression with Dichotomous and Dummy Variables292

12.6 Summing Up Chapter 12295

Writing Statistics 8: Multiple Regression and Correlation299

Appendix Statistical Tables301

Table 1: The Chi-Square Distribution303

Table 2: The t Distribution304

Table 3A: The F Distribution: p = .05305

Table 3B: The F Distribution: p = .01306

Table 3C: The F Distribution: p = .001307

Glossary309

Bibliography325

Index329