A user-friendly, hands-on guide to recognizing and conducting proper research techniques in data collection Offering a unique approach to numerical research methods, Analyzing Quantitative Data: An Introduction for Social Researchers presents readers with the necessary statistical applications for carrying out the key phases of conducting and evaluating a research project. The book guides readers through the steps of data analysis, from organizing raw data to utilizing descriptive statistics and tests of significance, drawing valid conclusions, and writing research reports. The author successfully provides a presentation that is accessible and hands-on rather than heavily theoretical, outlining the key quantitative processes and the use of software to successfully draw valid conclusions from gathered data. In its discussion of methods for organizing data, the book includes suggestions for coding and entry into spreadsheets or databases while also introducing commonly used descriptive statistics and clarifying their roles in data analysis. Next, inferential statistics is explored in-depth with explanations of and instructions for performing chi-square tests, t-tests, analyses of variance, correlation and regression analyses, and a number of advanced statistical procedures. Each chapter contains explanations of when to use the tests described, relevant formulas, and sample computations. The book concludes with guidance on extracting meaningful conclusions from statistical tests and writing research reports that describe procedures and analyses. Throughout the book, Statistical Resources for SPSS® sections provide fundamental instruction for using SPSS® to obtain the results presented. Where necessary, the author provides basic theoretical explanations for distributions and background information regarding formulas. Each chapter concludes with practice problems, and a related website features derivations of the book's formulas along with additional resources for performing the discussed processes. Analyzing Quantitative Data is an excellent book for social sciences courses on data analysis and research methods at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians and practitioners working in the fields of education, medicine, business and public service who analyze, interpret, and evaluate data in their daily work.

Table of Contents:
Preface xiii Part I Summarizing Data 1 1 Data Organization 3 1.1 Introduction 3 1.2 Consideration of Variables 4 1.2.1 Units of Analysis 4 1.2.2 Variables 4 Roles of Variables 5 Variable Relationships 6 Causal Time Order 6 Intervening Variables 7 The Nature of Data 8 Categorical Variables 8 Continuous Variables 9 Levels of Measurement 11 1.2.3 Attributes 13 1.3 Coding 15 1.3.1 Coding Categorical Data 15 1.3.2 Coding Ordinal Data 17 1.4 Data Manipulations 18 1.4.1 Filtering Subjects 18 1.4.2 Splitting Datasets 19 1.4.3 Calculations with Data 19 Basic Operations 19 Combining Multiple Indicators 20 1.5 Conclusion 20 Statistical Resources for SPSS® 21 Review Questions 29 2 Descriptive Statistics for Categorical Data 33 2.1 Introduction 33 2.2 Frequency Tables 35 2.2.1 Using Existing Categories 35 2.2.2 Creating Categories 35 2.3 Crosstabulations 37 2.3.1 Basic (Single-Layer) Crosstabulations 37 2.3.2 Multilayer Crosstabulations 39 Split Crosstabulations 40 Nested Crosstabulations 42 2.4 Graphs and Charts 44 2.4.1 Bar Graphs 45 Basic Bar Graphs 45 Clustered and Stacked Bar Graphs 46 2.4.2 Pie Charts 48 Basic Pie Chart 48 Paneled Pie Charts 48 2.5 Conclusion 50 Statistical Resources for SPSS 50 Review Questions 57 3 Descriptive Statistics for Continuous Data 63 3.1 Introduction 63 3.2 Frequencies 64 3.2.1 Frequency Histograms 64 Paneled Histograms 65 Stacked Histograms 67 Frequency Polygons 68 3.2.2 Stem-and-Leaf Charts 68 3.3 Measures of Central Tendency 70 3.3.1 Mean 70 3.3.2 Median 71 3.3.3 Mode 71 3.3.4 Deciding between Measures of Central Tendency 72 3.4 Measures of Dispersion 73 3.4.1 Maximum and Minimum 73 3.4.2 Range 73 3.4.3 Variance and Standard Deviation 75 Basic Formulas 76 Raw-Score Formulas 78 3.5 Standardized Scores 79 3.5.1 Computing Standardized Scores 80 3.5.2 Using Standardized Scores 82 3.6 Conclusion 88 Statistical Resources for SPSS 89 Review Questions 95 Part II Statistical Tests 101 4 Evaluating Statistical Significance 103 4.1 Introduction 103 4.2 Central Limit Theorem 104 4.2.1 Definition of the Central Limit Theorem 104 4.2.2 Demonstrating the Central Limit Theorem 106 4.2.3 Limitations of the Central Limit Theorem 107 4.3 Statistical Significance 107 4.3.1 The Importance of Good Sampling 108 Random Sampling 109 Sample Size 109 4.3.2 Identifying a Significant Difference 110 Probability Values 111 Alpha (α) and Critical Values 111 Confidence Intervals and Distribution Tails 112 Type I and Type II Errors 113 4.4 The Roles of Hypotheses 115 4.4.1 The Research and Null Hypotheses 116 Accepting the Null Hypothesis 117 Rejecting the Null Hypothesis 118 4.4.2 Unexpected Results 119 4.5 Conclusion 119 Statistical Resources for SPSS 120 Review Questions 122 5 The Chi-Square Test: Comparing Category Frequencies 125 5.1 Introduction 125 5.2 The Chi-Square Distribution 126 5.2.1 The Chi-Square Distribution versus the Normal Distribution 127 5.2.2 Variations of the Chi-Square Distribution 127 5.2.3 Chi-Square Probabilities 129 5.3 Performing Chi-Square Tests 130 5.3.1 One-Variable Chi-Square Test 131 The One-Variable Chi-Square Formula 132 Interpreting the One-Variable Calculated Chi-Square Value 134 5.3.2 Two-Variable Chi-Square Test 135 The Two-Variable Chi-Square Formula 136 Interpreting the Two-Variable Calculated Chi-Square Value 136 5.3.3 Three-or-More-Variable Chi-Square 139 Three-or-More-Variable Chi-Square Formulas 141 5.4 Post Hoc Testing 143 5.4.1 One-Variable Chi-Square Post Hoc Tests 144 5.4.2 Two-Variable Chi-Square Post Hoc Tests 144 5.4.3 Three-or-More-Variable Chi-Square Post Hoc Tests 145 5.5 Confidence Intervals 146 5.6 Explaining Results of the Chi-Square Test 147 5.7 Conclusion 148 Statistical Resources for SPSS 149 Review Questions 155 6 The t Test: Comparing Continuous-Variable Data Among Dichotomous Groups 159 6.1 Introduction 159 6.2 The t Distribution 160 6.3 Performing t Tests 161 6.3.1 One-Sample t Tests 162 One-Sample t-Test Formulas 162 Interpreting the One-Sample Calculated t Value 163 6.3.2 Paired (Dependent)-Samples t Test 165 Paired-Samples t-Test Formulas 166 Interpreting the Paired-Samples Calculated t Value 168 6.3.3 Independent-Samples t Test 169 Independent-Samples t-Test Formulas 169 Interpreting the Independent-Samples Calculated t Value 171 6.4 Confidence Intervals 172 6.5 Explaining Results of the t Test 173 6.6 Conclusion 174 Statistical Resources for SPSS 175 Review Questions 183 7 Analysis of Variance: Comparing Continuous-Variable Data Among Nondichotomous Groups 187 7.1 Introduction 187 7.2 The F Distribution 189 7.2.1 The F Distribution versus the Normal Distribution 189 7.2.2 Variations in the F Distribution 190 7.2.3 F Probabilities 191 7.3 Performing ANOVAs 192 7.3.1 One-Way ANOVA 192 One-Way ANOVA Formulas 193 Interpreting the One-Way Calculated F Value 197 7.3.2 Two-or-More-Way ANOVA 199 Factorial Designs 199 Main Effects and Interaction Effects 201 Two-Way ANOVA Formulas 205 Interpreting the Two-Way Calculated F Value 212 7.4 Post Hoc Testing 214 7.4.1 One-Way ANOVA Post Hoc Tests 215 7.4.2 Two-or-More-Way ANOVA Post Hoc Tests 216 7.5 Confidence Intervals 217 7.6 Explaining Results of the ANOVA 218 7.7 Conclusion 219 Statistical Resources for SPSS 220 Review Questions 226 8 Correlation and Regression: Comparing Changes Among Continuous-Variable Scores 231 8.1 Introduction 231 8.2 Bivariate Relationships 233 8.2.1 Bivariate Regression 234 8.2.2 Pairwise Correlation 238 The Pairwise Correlation Coefficient 238 The Coefficient of Determination 241 8.2.3 Curvilinear Relationships 242 8.3 Multivariate Relationships 244 8.3.1 Multiple Regression 245 8.3.2 Multiple Correlation 247 The Multiple-Correlation Coefficient 247 The Coefficient of Multiple Determination 248 8.3.3 Partial and Part Correlations 249 Partial Correlation 250 Part Correlation 252 8.4 The Phi Coefficient 253 8.5 Explaining Results of Correlation–Regression Analysis 255 8.5.1 Regression and Correlation 255 8.5.2 Relationships between Dichotomous Variables 257 8.6 Conclusion 258 Statistical Resources for SPSS 259 Review Questions 267 9 Advanced Statistical Analyses 273 9.1 Introduction 273 9.2 Repeated-Measures Analysis of Variance 274 9.2.1 Capabilities of Repeated-Measures ANOVA 274 9.2.2 Performing a Repeated-Measures ANOVA 275 9.3 Multiple Analysis of Variance 278 9.3.1 Capabilities of MANOVA 279 9.3.2 Performing a MANOVA 280 9.4 Analysis of Covariance 282 9.4.1 Capabilities of ANCOVA 283 9.4.2 Performing an ANCOVA 284 9.5 Discriminant Analysis 286 9.5.1 Capabilities of Discriminant Analysis 287 9.5.2 Performing a Discriminant Analysis 289 9.6 Conclusion 290 Statistical Resources for SPSS 290 Review Questions 299 Part III Applying Data 303 10 Drawing Conclusions 305 10.1 Introduction 305 10.2 Accepting and Rejecting Hypotheses 306 10.2.1 The Null Hypothesis–Research Hypothesis Relationship 306 10.2.2 Matching Null and Research Hypotheses 307 10.2.3 Different Null and Research Hypotheses 308 10.3 Drawing Conclusions from Results 310 10.3.1 Summarizing 311 10.3.2 Reflecting 313 10.3.3 Speculating 314 10.4 Cautions 315 10.4.1 Alternate Explanations of Causation 316 10.4.2 High Alpha Values 319 10.4.3 The Ecological Fallacy 320 10.4.4 Reductionism 322 10.5 Conclusion 323 Review Questions 324 11 Writing Research Reports 327 11.1 Introduction 327 11.2 Tone 328 11.2.1 Language 329 11.2.2 Presentation of Facts 332 11.3 Sections of the Research Report 334 11.3.1 Presentation of Hypothesis 334 Filling a Gap in Knowledge 335 Building on Past Research 336 Contradicting Past Findings 336 Connecting Past Findings 338 11.3.2 Description of Methods 339 Subjects 339 Population 339 Sampling Methods 340 Measures 341 Procedure 342 11.3.3 Presentation of Results 344 11.3.4 Presentation of Conclusions 348 11.4 Conclusion 348 Review Questions 348 Appendixes 353 Appendix A: Z-Score Table 355 Appendix B: Table for Critical χ2 Values 357 Appendix C: Table for Critical t Values 359 Appendix D: Table for Critical F Values 361 References 369 Answers to Review Questions 371 Index 391