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 SPSSi sections provide fundamental instruction for using SPSSi 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.
Preface xiii Part I. Summarizing Data 1 1. Data Organization 3 1.1 Introduction 3 1.2 Consideration of Variables 4 1.3 Coding 15 1.4 Data Manipulations 18 1.5 Conclusion 20 2. Descriptive Statistics for Categorical Data 33 2.1 Introduction 33 2.2 Frequency Tables 35 2.3 Crosstabulations 37 2.4 Graphs and Charts 45 2.5 Conclusion 50 3. Descriptive Statistics for Continuous Data 63 3.1 Introduction 63 3.2 Frequencies 64 3.3 Measures of Central Tendency 70 3.4 Measures of Dispersion 73 3.5 Standardized Scores 79 3.6 Conclusion 88 Part II. Statistical Tests 101 4. Evaluating Statistical Significance 103 4.1 Introduction 103 4.2 Central Limit Theorem 104 4.3 Statistical Significance 107 4.4 The Roles of Hypotheses 115 4.5 Conclusion 119 5. The Chi-Square Test: Comparing Category Frequencies 125 5.1 Introduction 125 5.2 The Chi-Square Distribution 126 5.3 Performing Chi-Square Tests 130 5.4 Post Hoc Testing 143 5.5 Confidence Intervals 146 5.6 Explaining Results of the Chi-Square Test 147 5.7 Conclusion 148 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 6.4 Confidence Intervals 172 6.5 Explaining Results of the t Test 173 6.6 Conclusion 174 7. Analysis of Variance: Comparing Continuous-Variable Data Among Nondichotomous Groups 187 7.1 Introduction 187 7.2 The F Distribution 189 7.3 Performing ANOVAs 192 7.4 Post Hoc Testing 214 7.5 Confidence Intervals 217 7.6 Explaining Results of the ANOVA 218 7.7 Conclusion 219 8. Correlation and Regression: Comparing Changes Among Continuous-Variable Scores 231 8.1 Introduction 231 8.2 Bivariate Relationships 233 8.3 Multivariate Relationships 244 8.4 The Phi Coefficient 253 8.5 Explaining Results of Correlation-Regression Analysis 255 8.6 Conclusion 258 9. Advanced Statistical Analyses 273 9.1 Introduction 273 9.2 Repeated-Measures Analysis of Variance 274 9.3 Multiple Analysis of Variance 278 9.4 Analysis of Covariance 283 9.5 Discriminant Analysis 286 9.6 Conclusion 290 Part III. Applying Data 303 10. Drawing Conclusions 305 10.1 Introduction 305 10.2 Accepting and Rejecting Hypotheses 306 10.3 Drawing Conclusions from Results 310 10.4 Cautions 315 10.5 Conclusion 323 11. Writing Research Reports 327 11.1 Introduction 327 11.2 Tone 328 11.3 Sections of the Research Report 334 11.4. Conclusion 348 Appendixes 353 Appendix A. Z-Score Table 355 Appendix B. Table for Critical X2 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
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