SOCIAL STATISTICS FOR A DIVERSE SOCIETY SEVENTH EDITIONPDF电子书下载

1.The What and the Why of Statistics 1

The Research Process 2

Asking Research Questions 3

The Role of Theory 4

Formulating the Hypotheses 5

Independent and Dependent Variables：Causality 7

Independent and Dependent Variables：Guidelines 9

Collecting Data 10

Levels of Measurement 11

Nominal Level of Measurement 11

Ordinal Level of Measurement 12

Interval-Ratio Level of Measurement 12

Cumulative Property of Levels of Measurement 13

Levels of Measurement of Dichotomous Variables 13

Discrete and Continuous Variables 16

A Closer Look 1.1：A Cautionary Note：Measurement Error 16

Analyzing Data and Evaluating the Hypotheses 17

Descriptive and Inferential Statistics 17

Evaluating the Hypotheses 18

Looking at Social Differences 19

A Closer Look 1.2：A Tale of Simple Arithmetic：How Culture May Influence How We Count 20

A Closer Look 1.3：Are You Anxious About Statistics？ 21

2.Organization of Information：Frequency Distributions 27

Frequency Distributions 28

Proportions and Percentages 29

Percentage Distributions 31

Comparisons 32

Statistics in Practice：Labor Force Participation Among Foreign Born 33

The Construction of Frequency Distributions 35

Frequency Distributions for Nominal Variables 37

Frequency Distributions for Ordinal Variables 37

Frequency Distributions for Interval-Ratio Variables 38

Cumulative Distributions 43

A Closer Look 2.1：Real Limits，Stated Limits，and Midpoints ofClass Intervals 44

Rates 47

Statistics in Practice：Civilian Labor Force Participation Rates Over Time 48

Reading the Research Literature：Statistical Tables 48

Basic Principles 49

Tables With a Different Format 51

Conclusion 52

3.Graphic Presentation 65

The Pie Chart：Race and Ethnicity of the Elderly 66

The Bar Graph：Marital Status of the Elderly 68

The Statistical Map：The Geographic Distribution of the Elderly 70

The Histogram 71

Statistics in Practice：Gender and Age 73

The Line Graph 75

Time-Series Charts 77

A Closer Look 3.1：A Cautionary Note：Distortions in Graphs 79

Statistics in Practice：The Graphic Presentation of Education 81

4.Measures of Central Tendency 96

The Mode 97

The Median 100

Finding the Median in Sorted Data 101

An Odd Number of Cases 101

An Even Number of Cases 103

Finding the Median in Frequency Distributions 104

Statistics in Practice：Gendered Income Inequality 105

Locating Percentiles in a Frequency Distribution 106

The Mean 108

Calculating the Mean 109

A Closer Look 4.1：Finding the Mean in a Frequency Distribution 110

Understanding Some Important Properties of the Arithmetic Mean 113

Interval-Ratio Level of Measurement 113

Center of Gravity 113

Sensitivity to Extremes 113

The Shape of the Distribution：Television，Education，and Siblings 116

The Symmetrical Distribution 116

The Positively Skewed Distribution 117

The Negatively Skewed Distribution 119

Guidelines for Identifying the Shape of a Distribution 120

Considerations for Choosing a Measure of Central Tendency 121

Level of Measurement 121

Skewed Distribution 121

Symmetrical Distribution 122

A Closer Look 4.2：A Cautionary Note：Representing Income 122

5.Measures of Variability 135

The Importance of Measuring Variability 136

The Index of Qualitative Variation：A Brief Introduction 138

Steps for Calculating the IQV 139

A Closer Look 5.1：Statistics in Practice：Diversity at Berkeley Through the Years 140

Expressing the IQV as a Percentage 141

Statistics in Practice：Diversity in U.S.Society 142

The Range 143

The Interquartile Range：Increases in Elderly Population 145

The Box Plot 147

The Variance and the Standard Deviation：Changes in the Elderly Population 151

Calculating the Deviation From the Mean 152

Calculating the Variance and the Standard Deviation 154

Focus on Interpretation：GDP for Selected Countries 156

Considerations for Choosing a Measure of Variation 159

Reading the Research Literature：Differences in College Aspirations and Expectations Among Latino Adolescents 160

6.The Normal Distribution 177

Properties of the Normal Distribution 178

Empirical Distributions Approximating the Normal Distribution 178

An Example：Final Grades in Statistics 179

Areas Under the Normal Curve 180

Interpreting the Standard Deviation 181

Standard （Z） Scores 182

Transforming a Raw Score Into a Z Score 182

Transforming a Z Score Into a Raw Score 184

The Standard Normal Distribution 185

The Standard Normal Table 185

The Structure of the Standard Normal Table 186

Transforming Z Scores Into Proportions （or Percentages） 187

Finding the Area Between the Mean and a Specified Positive Z Score 188

Finding the Area Between the Mean and a Specified Negative Z Score 188

Finding the Area Above a Positive Z Score or Below a Negative Z Score 189

Transforming Proportions （or Percentages） Into Z Scores 190

Finding a Z Score Bounding an Area Above It 191

Finding a Z Score Bounding an Area Below It 192

Working With Percentiles in a Normal Distribution 193

Finding the Percentile Rank of a Score Higher Than the Mean 193

Finding the Percentile Rank of a Score Lower Than the Mean 194

Finding the Raw Score Associated With a Percentile Higher Than 50 195

Finding the Raw Score Associated With a Percentile Lower Than 50 196

A Final Note 197

7.Sampling and Sampling Distributions 206

Aims of Sampling 207

Some Basic Principles of Probability 209

Probability Defined 209

The Relative Frequency Method 209

The Normal Distribution and Probabilities 210

Probability Sampling 211

The Simple Random Sample 211

The Systematic Random Sample 213

The Stratified Random Sample 214

A Closer Look 7.1：Disproportionate Stratified Samples and Diversity 215

The Concept of the Sampling Distribution 216

The Population 217

The Sample 218

The Dilemma 219

The Sampling Distribution 219

The Sampling Distribution of the Mean 219

An Illustration 219

Review 222

The Mean of the Sampling Distribution 222

The Standard Error of the Mean 223

The Central Limit Theorem 224

The Size of the Sample 227

The Significance of the Sampling Distribution and the Central Limit Theorem 227

Statistics in Practice：The Central Limit Theorem 229

8.Estimation 237

Estimation Defined 238

Reasons for Estimation 239

Point and Interval Estimation 239

Procedures for Estimating Confidence Intervals for Means 240

A Closer Look 8.1：Estimation as a Type of Inference 241

Determining the Confidence Interval 242

Calculating the Standard Error of the Mean 243

Deciding on the Level of Confidence and Finding theCorresponding Z Value 243

Calculating the Confidence Interval 243

Interpreting the Results 244

Reducing Risk 244

Estimating Sigma 246

Calculating the Estimated Standard Error of the Mean 247

Deciding on the Level of Confidence and Finding theCorresponding Z Value 247

Calculating the Confidence Interval 247

Interpreting the Results 247

Sample Size and Confidence Intervals 247

A Closer Look 8.2：What Affects Confidence IntervalWidth？Summary 249

Statistics in Practice：Hispanic Migration and Earnings 250

Confidence Intervals for Proportions 253

Procedures for Estimating Proportions 254

Calculating the Estimated Standard Error of the Proportion 255

Deciding on the Desired Level of Confidence and Findingthe Corresponding Z Value 255

Calculating the Confidence Interval 255

Interpreting the Results 255

Statistics in Practice：The 2012 Benghazi Terrorist Attack Investigation 256

Calculating the Estimated Standard Error of the Proportion 256

Deciding on the Desired Level of Confidence and Finding theCorresponding Z Value 257

Calculating the Confidence Interval 257

Interpreting the Results 257

A Closer Look 8.3：A Cautionary Note：The Margin of Error 258

9.Testing Hypotheses 267

Assumptions of Statistical Hypothesis Testing 268

Stating the Research and Null Hypotheses 269

The Research Hypothesis （H1） 269

The Null Hypothesis （H0） 269

More About Research Hypotheses：One- and Two-Tailed Tests 270

Determining What Is Sufficiently Improbable：Probability Values and Alpha 271

The Five Steps in Hypothesis Testing：A Summary 275

Errors in Hypothesis Testing 276

The t Statistic and Estimating the Standard Error 278

The t Distribution and Degrees of Freedom 278

Comparing the t and Z Statistics 279

Statistics in Practice：The Earnings of White Women 280

Testing Hypotheses About Two Samples 281

The Assumption of Independent Samples 282

Stating the Research and Null Hypotheses 282

The Sampling Distribution of the Difference Between Means 283

Estimating the Standard Error 284

Calculating the Estimated Standard Error 284

The t Statistic 285

Calculating the Degrees of Freedom for a Difference Between Means Test 285

A Closer Look 9.1：Calculating the Estimated Standard Error andthe Degrees of Freedom（df）When the Population VariancesAre Assumed to Be Unequal 285

The Five Steps in Hypothesis Testing About Difference Between Means：A Summary 286

Focus on Interpretation：Cigarette Use Among Teens 287

Testing the Significance of the Difference Between Two Sample Proportions 289

Statistics in Practice：Comparing First- and Second-GenerationHispanic Americans 289

Focus on Interpretation：First- and Second-Generation Asian Americans 291

A Closer Look 9.2：A Cautionary Note：Is There a Significant Difference？ 292

Reading the Research Literature：Reporting the Results ofStatistical Hypothesis Testing 292

10.Bivariate Tables 303

Independent and Dependent Variables 304

How to Construct a Bivariate Table：Race and Home Ownership 305

How to Compute Percentages in a Bivariate Table 307

Calculating Percentages Within Each Category of the Independent Variable 308

Comparing the Percentages Across Different Categories of theIndependent Variable 308

A Closer Look 10.1：Percentaging a Bivariate Table 309

How to Deal With Ambiguous Relationships Between Variables 310

Reading the Research Literature：Place of Death in America 312

The Properties of a Bivariate Relationship 315

The Existence of the Relationship 316

The Strength of the Relationship 317

The Direction of the Relationship 317

Elaboration 319

Testing for Nonspuriousness：Firefighters and Property Damage 320

An Intervening Relationship：Religion and Attitude Toward Abortion 323

Conditional Relationships：More on Abortion 328

The Limitations of Elaboration 330

Statistics in Practice：Family Support for the Transition From High School 331

11.The Chi-Square Test and Measures of Association 347

The Concept of Chi-Square as a Statistical Test 350

The Concept of Statistical Independence 350

The Structure of Hypothesis Testing With Chi-Square 351

The Assumptions 351

Stating the Research and the Null Hypotheses 351

The Concept of Expected Frequencies 352

Calculating the Expected Frequencies 352

Calculating the Obtained Chi-Square 354

The Sampling Distribution of Chi-Square 355

Determining the Degrees of Freedom 356

Making a Final Decision 357

Review 358

A Closer Look 11.1：A Cautionary Note：Sample Size and Statistical Significance for Chi-Square 359

Focus on Interpretation：Education and Health Assessment 360

Reading the Research Literature：Violent Offense Onset by Gender，Race，and Age 362

Proportional Reduction of Error：A Brief Introduction 363

A Closer Look 11.2：What Is Strong？What Is Weak？A Guide to Interpretation 366

Lambda：A Measure of Association for Nominal Variables 367

A Method for Calculating Lambda 368

Some Guidelines for Calculating Lambda 369

Cramer’s V：A Chi-Square-Related Measure of Association for Nominal Variables 370

Focus on Interpretation：Gamma and Kendall’s Tau-b 370

Using Ordinal Measures With Dichotomous Variables 372

Focus on Interpretation：The Gender Gap in Gun Control 373

12.Analysis of Variance 388

Understanding Analysis of Variance 389

The Structure of Hypothesis Testing With ANOVA 391

The Assumptions 391

Stating the Research and the Null Hypotheses and Setting Alpha 392

The Concepts of Between and Within Total Variance 392

A Closer Look 12.1：Decomposition of SST 394

The F Statistic 395

Making a Decision 397

The Five Steps in Hypothesis Testing：A Summary 397

A Closer Look 12.2：Assessing the Relationship Between Variables 399

Focus on Interpretation：Are Immigrants Good for America’s Economy？ 399

Reading the Research Literature：Self-Image and Ethnic Identification 400

Reading the Research Literature：Stresses and Strains Among Grandmother Caregivers 402

13.Regression and Correlation 413

The Scatter Diagram 415

Linear Relations and Prediction Rules 417

Constructing Straight-Line Graphs 420

Finding the Best-Fitting Line 422

Defining Error 423

The Residual Sum of Squares （∑e2） 423

The Least Squares Line 424

Review 424

Computing a and b for the Prediction Equation 424

Interpreting a and b 427

Statistics in Practice：Median Household Income and Criminal Behavior 429

A Closer Look 13.1：Understanding the Covariance 429

A Closer Look 13.2：A Note on Nonlinear Relationships 430

Methods for Assessing the Accuracy of Predictions 432

Prediction Errors 434

The Coefficient of Determination （r2） as a PRE Measure 437

Calculating r2 439

Testing the Significance of r2 Using ANOVA 441

Making a Decision 443

Pearson’s Correlation Coefficient （r） 443

Characteristics of Pearson’s r 444

Statistics in Practice：Teen Pregnancy and Social Inequality 445

Focus on Interpretation：The Marriage Penalty in Earnings 448

Multiple Regression 450

ANOVA for Multiple Linear Regression 453

A Closer Look 13.3：A Cautionary Note：Spurious Correlations and Confounding Effects 454

Appendix A.Table of Random Numbers 477

Appendix B.The Standard Normal Table 480

Appendix C.Distribution of t 484

Appendix D.Distribution of Chi-Square 486

Appendix E.Distribution of F 487

Appendix F.A Basic Math Review 489

Learning Check Solutions 494

Answers to Odd-Numbered Exercises 504

Glossary 546

Notes 551

Index 556