{"product_id":"analyzing-quantitative-data-an-introduction-for-social-researchers-hardback-9780470526835","title":"Analyzing Quantitative Data; An Introduction for Social Researchers (Hardback) 9780470526835","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eAnalyzing Quantitative Data\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eAn Introduction for Social Researchers\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eDebra Wetcher-Hendricks (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780470526835, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 5 August 2011\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e414 pages, Charts: 9 B\u0026amp;W, 0 Color; Drawings: 15 B\u0026amp;W, 0 Color; Screen captures: 30 B\u0026amp;W, 0 Color; Tables: 0 B\u0026amp;W, 0 Color; Graphs: 41 B\u0026amp;W, 0 Color\u003cbr\u003e24.4 x 16.3 x 2.5 cm, 0.767 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cb\u003eA user-friendly, hands-on guide to recognizing and conducting proper research techniques in data collection\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003e   \u003cp\u003eOffering a unique approach to numerical research methods, \u003ci\u003eAnalyzing Quantitative Data: An Introduction for Social Researchers\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eIn 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.\u003c\/p\u003e \u003cp\u003eThroughout 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.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eAnalyzing Quantitative Data\u003c\/i\u003e 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.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Summarizing Data 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Data Organization 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 3\u003c\/p\u003e \u003cp\u003e1.2 Consideration of Variables 4\u003c\/p\u003e \u003cp\u003e1.2.1 Units of Analysis 4\u003c\/p\u003e \u003cp\u003e1.2.2 Variables 4\u003c\/p\u003e \u003cp\u003eRoles of Variables 5\u003c\/p\u003e \u003cp\u003eVariable Relationships 6\u003c\/p\u003e \u003cp\u003eCausal Time Order 6\u003c\/p\u003e \u003cp\u003eIntervening Variables 7\u003c\/p\u003e \u003cp\u003eThe Nature of Data 8\u003c\/p\u003e \u003cp\u003eCategorical Variables 8\u003c\/p\u003e \u003cp\u003eContinuous Variables 9\u003c\/p\u003e \u003cp\u003eLevels of Measurement 11\u003c\/p\u003e \u003cp\u003e1.2.3 Attributes 13\u003c\/p\u003e \u003cp\u003e1.3 Coding 15\u003c\/p\u003e \u003cp\u003e1.3.1 Coding Categorical Data 15\u003c\/p\u003e \u003cp\u003e1.3.2 Coding Ordinal Data 17\u003c\/p\u003e \u003cp\u003e1.4 Data Manipulations 18\u003c\/p\u003e \u003cp\u003e1.4.1 Filtering Subjects 18\u003c\/p\u003e \u003cp\u003e1.4.2 Splitting Datasets 19\u003c\/p\u003e \u003cp\u003e1.4.3 Calculations with Data 19\u003c\/p\u003e \u003cp\u003eBasic Operations 19\u003c\/p\u003e \u003cp\u003eCombining Multiple Indicators 20\u003c\/p\u003e \u003cp\u003e1.5 Conclusion 20\u003c\/p\u003e \u003cp\u003eStatistical Resources for SPSS\u003csup\u003e®\u003c\/sup\u003e 21\u003c\/p\u003e \u003cp\u003eReview Questions 29\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Descriptive Statistics for Categorical Data 33\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 33\u003c\/p\u003e \u003cp\u003e2.2 Frequency Tables 35\u003c\/p\u003e \u003cp\u003e2.2.1 Using Existing Categories 35\u003c\/p\u003e \u003cp\u003e2.2.2 Creating Categories 35\u003c\/p\u003e \u003cp\u003e2.3 Crosstabulations 37\u003c\/p\u003e \u003cp\u003e2.3.1 Basic (Single-Layer) Crosstabulations 37\u003c\/p\u003e \u003cp\u003e2.3.2 Multilayer Crosstabulations 39\u003c\/p\u003e \u003cp\u003eSplit Crosstabulations 40\u003c\/p\u003e \u003cp\u003eNested Crosstabulations 42\u003c\/p\u003e \u003cp\u003e2.4 Graphs and Charts 44\u003c\/p\u003e \u003cp\u003e2.4.1 Bar Graphs 45\u003c\/p\u003e \u003cp\u003eBasic Bar Graphs 45\u003c\/p\u003e \u003cp\u003eClustered and Stacked Bar Graphs 46\u003c\/p\u003e \u003cp\u003e2.4.2 Pie Charts 48\u003c\/p\u003e \u003cp\u003eBasic Pie Chart 48\u003c\/p\u003e \u003cp\u003ePaneled Pie Charts 48\u003c\/p\u003e \u003cp\u003e2.5 Conclusion 50\u003c\/p\u003e \u003cp\u003eStatistical Resources for SPSS 50\u003c\/p\u003e \u003cp\u003eReview Questions 57\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Descriptive Statistics for Continuous Data 63\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 63\u003c\/p\u003e \u003cp\u003e3.2 Frequencies 64\u003c\/p\u003e \u003cp\u003e3.2.1 Frequency Histograms 64\u003c\/p\u003e \u003cp\u003ePaneled Histograms 65\u003c\/p\u003e \u003cp\u003eStacked Histograms 67\u003c\/p\u003e \u003cp\u003eFrequency Polygons 68\u003c\/p\u003e \u003cp\u003e3.2.2 Stem-and-Leaf Charts 68\u003c\/p\u003e \u003cp\u003e3.3 Measures of Central Tendency 70\u003c\/p\u003e \u003cp\u003e3.3.1 Mean 70\u003c\/p\u003e \u003cp\u003e3.3.2 Median 71\u003c\/p\u003e \u003cp\u003e3.3.3 Mode 71\u003c\/p\u003e \u003cp\u003e3.3.4 Deciding between Measures of Central Tendency 72\u003c\/p\u003e \u003cp\u003e3.4 Measures of Dispersion 73\u003c\/p\u003e \u003cp\u003e3.4.1 Maximum and Minimum 73\u003c\/p\u003e \u003cp\u003e3.4.2 Range 73\u003c\/p\u003e \u003cp\u003e3.4.3 Variance and Standard Deviation 75\u003c\/p\u003e \u003cp\u003eBasic Formulas 76\u003c\/p\u003e \u003cp\u003eRaw-Score Formulas 78\u003c\/p\u003e \u003cp\u003e3.5 Standardized Scores 79\u003c\/p\u003e \u003cp\u003e3.5.1 Computing Standardized Scores 80\u003c\/p\u003e \u003cp\u003e3.5.2 Using Standardized Scores 82\u003c\/p\u003e \u003cp\u003e3.6 Conclusion 88\u003c\/p\u003e \u003cp\u003eStatistical Resources for SPSS 89\u003c\/p\u003e \u003cp\u003eReview Questions 95\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Statistical Tests 101\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Evaluating Statistical Significance 103\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 103\u003c\/p\u003e \u003cp\u003e4.2 Central Limit Theorem 104\u003c\/p\u003e \u003cp\u003e4.2.1 Definition of the Central Limit Theorem 104\u003c\/p\u003e \u003cp\u003e4.2.2 Demonstrating the Central Limit Theorem 106\u003c\/p\u003e \u003cp\u003e4.2.3 Limitations of the Central Limit Theorem 107\u003c\/p\u003e \u003cp\u003e4.3 Statistical Significance 107\u003c\/p\u003e \u003cp\u003e4.3.1 The Importance of Good Sampling 108\u003c\/p\u003e \u003cp\u003eRandom Sampling 109\u003c\/p\u003e \u003cp\u003eSample Size 109\u003c\/p\u003e \u003cp\u003e4.3.2 Identifying a Significant Difference 110\u003c\/p\u003e \u003cp\u003eProbability Values 111\u003c\/p\u003e \u003cp\u003eAlpha (α) and Critical Values 111\u003c\/p\u003e \u003cp\u003eConfidence Intervals and Distribution Tails 112\u003c\/p\u003e \u003cp\u003eType I and Type II Errors 113\u003c\/p\u003e \u003cp\u003e4.4 The Roles of Hypotheses 115\u003c\/p\u003e \u003cp\u003e4.4.1 The Research and Null Hypotheses 116\u003c\/p\u003e \u003cp\u003eAccepting the Null Hypothesis 117\u003c\/p\u003e \u003cp\u003eRejecting the Null Hypothesis 118\u003c\/p\u003e \u003cp\u003e4.4.2 Unexpected Results 119\u003c\/p\u003e \u003cp\u003e4.5 Conclusion 119\u003c\/p\u003e \u003cp\u003eStatistical Resources for SPSS 120\u003c\/p\u003e \u003cp\u003eReview Questions 122\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 The Chi-Square Test: Comparing Category Frequencies 125\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 125\u003c\/p\u003e \u003cp\u003e5.2 The Chi-Square Distribution 126\u003c\/p\u003e \u003cp\u003e5.2.1 The Chi-Square Distribution versus the Normal Distribution 127\u003c\/p\u003e \u003cp\u003e5.2.2 Variations of the Chi-Square Distribution 127\u003c\/p\u003e \u003cp\u003e5.2.3 Chi-Square Probabilities 129\u003c\/p\u003e \u003cp\u003e5.3 Performing Chi-Square Tests 130\u003c\/p\u003e \u003cp\u003e5.3.1 One-Variable Chi-Square Test 131\u003c\/p\u003e \u003cp\u003eThe One-Variable Chi-Square Formula 132\u003c\/p\u003e \u003cp\u003eInterpreting the One-Variable Calculated Chi-Square Value 134\u003c\/p\u003e \u003cp\u003e5.3.2 Two-Variable Chi-Square Test 135\u003c\/p\u003e \u003cp\u003eThe Two-Variable Chi-Square Formula 136\u003c\/p\u003e \u003cp\u003eInterpreting the Two-Variable Calculated Chi-Square Value 136\u003c\/p\u003e \u003cp\u003e5.3.3 Three-or-More-Variable Chi-Square 139\u003c\/p\u003e \u003cp\u003eThree-or-More-Variable Chi-Square Formulas 141\u003c\/p\u003e \u003cp\u003e5.4 Post Hoc Testing 143\u003c\/p\u003e \u003cp\u003e5.4.1 One-Variable Chi-Square Post Hoc Tests 144\u003c\/p\u003e \u003cp\u003e5.4.2 Two-Variable Chi-Square Post Hoc Tests 144\u003c\/p\u003e \u003cp\u003e5.4.3 Three-or-More-Variable Chi-Square Post Hoc Tests 145\u003c\/p\u003e \u003cp\u003e5.5 Confidence Intervals 146\u003c\/p\u003e \u003cp\u003e5.6 Explaining Results of the Chi-Square Test 147\u003c\/p\u003e \u003cp\u003e5.7 Conclusion 148\u003c\/p\u003e \u003cp\u003eStatistical Resources for SPSS 149\u003c\/p\u003e \u003cp\u003eReview Questions 155\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 The \u003ci\u003et \u003c\/i\u003eTest: Comparing Continuous-Variable Data Among Dichotomous Groups 159\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 159\u003c\/p\u003e \u003cp\u003e6.2 The \u003ci\u003et \u003c\/i\u003eDistribution 160\u003c\/p\u003e \u003cp\u003e6.3 Performing \u003ci\u003et \u003c\/i\u003eTests 161\u003c\/p\u003e \u003cp\u003e6.3.1 One-Sample \u003ci\u003et \u003c\/i\u003eTests 162\u003c\/p\u003e \u003cp\u003eOne-Sample \u003ci\u003et\u003c\/i\u003e-Test Formulas 162\u003c\/p\u003e \u003cp\u003eInterpreting the One-Sample Calculated \u003ci\u003et \u003c\/i\u003eValue 163\u003c\/p\u003e \u003cp\u003e6.3.2 Paired (Dependent)-Samples \u003ci\u003et \u003c\/i\u003eTest 165\u003c\/p\u003e \u003cp\u003ePaired-Samples \u003ci\u003et\u003c\/i\u003e-Test Formulas 166\u003c\/p\u003e \u003cp\u003eInterpreting the Paired-Samples Calculated \u003ci\u003et \u003c\/i\u003eValue 168\u003c\/p\u003e \u003cp\u003e6.3.3 Independent-Samples \u003ci\u003et \u003c\/i\u003eTest 169\u003c\/p\u003e \u003cp\u003eIndependent-Samples \u003ci\u003et\u003c\/i\u003e-Test Formulas 169\u003c\/p\u003e \u003cp\u003eInterpreting the Independent-Samples Calculated \u003ci\u003et \u003c\/i\u003eValue 171\u003c\/p\u003e \u003cp\u003e6.4 Confidence Intervals 172\u003c\/p\u003e \u003cp\u003e6.5 Explaining Results of the \u003ci\u003et \u003c\/i\u003eTest 173\u003c\/p\u003e \u003cp\u003e6.6 Conclusion 174\u003c\/p\u003e \u003cp\u003eStatistical Resources for SPSS 175\u003c\/p\u003e \u003cp\u003eReview Questions 183\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Analysis of Variance: Comparing Continuous-Variable Data Among Nondichotomous Groups 187\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 187\u003c\/p\u003e \u003cp\u003e7.2 The \u003ci\u003eF \u003c\/i\u003eDistribution 189\u003c\/p\u003e \u003cp\u003e7.2.1 The \u003ci\u003eF \u003c\/i\u003eDistribution versus the Normal Distribution 189\u003c\/p\u003e \u003cp\u003e7.2.2 Variations in the \u003ci\u003eF \u003c\/i\u003eDistribution 190\u003c\/p\u003e \u003cp\u003e7.2.3 \u003ci\u003eF \u003c\/i\u003eProbabilities 191\u003c\/p\u003e \u003cp\u003e7.3 Performing ANOVAs 192\u003c\/p\u003e \u003cp\u003e7.3.1 One-Way ANOVA 192\u003c\/p\u003e \u003cp\u003eOne-Way ANOVA Formulas 193\u003c\/p\u003e \u003cp\u003eInterpreting the One-Way Calculated \u003ci\u003eF \u003c\/i\u003eValue 197\u003c\/p\u003e \u003cp\u003e7.3.2 Two-or-More-Way ANOVA 199\u003c\/p\u003e \u003cp\u003eFactorial Designs 199\u003c\/p\u003e \u003cp\u003eMain Effects and Interaction Effects 201\u003c\/p\u003e \u003cp\u003eTwo-Way ANOVA Formulas 205\u003c\/p\u003e \u003cp\u003eInterpreting the Two-Way Calculated \u003ci\u003eF \u003c\/i\u003eValue 212\u003c\/p\u003e \u003cp\u003e7.4 Post Hoc Testing 214\u003c\/p\u003e \u003cp\u003e7.4.1 One-Way ANOVA Post Hoc Tests 215\u003c\/p\u003e \u003cp\u003e7.4.2 Two-or-More-Way ANOVA Post Hoc Tests 216\u003c\/p\u003e \u003cp\u003e7.5 Confidence Intervals 217\u003c\/p\u003e \u003cp\u003e7.6 Explaining Results of the ANOVA 218\u003c\/p\u003e \u003cp\u003e7.7 Conclusion 219\u003c\/p\u003e \u003cp\u003eStatistical Resources for SPSS 220\u003c\/p\u003e \u003cp\u003eReview Questions 226\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Correlation and Regression: Comparing Changes Among Continuous-Variable Scores 231\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 231\u003c\/p\u003e \u003cp\u003e8.2 Bivariate Relationships 233\u003c\/p\u003e \u003cp\u003e8.2.1 Bivariate Regression 234\u003c\/p\u003e \u003cp\u003e8.2.2 Pairwise Correlation 238\u003c\/p\u003e \u003cp\u003eThe Pairwise Correlation Coefficient 238\u003c\/p\u003e \u003cp\u003eThe Coefficient of Determination 241\u003c\/p\u003e \u003cp\u003e8.2.3 Curvilinear Relationships 242\u003c\/p\u003e \u003cp\u003e8.3 Multivariate Relationships 244\u003c\/p\u003e \u003cp\u003e8.3.1 Multiple Regression 245\u003c\/p\u003e \u003cp\u003e8.3.2 Multiple Correlation 247\u003c\/p\u003e \u003cp\u003eThe Multiple-Correlation Coefficient 247\u003c\/p\u003e \u003cp\u003eThe Coefficient of Multiple Determination 248\u003c\/p\u003e \u003cp\u003e8.3.3 Partial and Part Correlations 249\u003c\/p\u003e \u003cp\u003ePartial Correlation 250\u003c\/p\u003e \u003cp\u003ePart Correlation 252\u003c\/p\u003e \u003cp\u003e8.4 The Phi Coefficient 253\u003c\/p\u003e \u003cp\u003e8.5 Explaining Results of Correlation–Regression Analysis 255\u003c\/p\u003e \u003cp\u003e8.5.1 Regression and Correlation 255\u003c\/p\u003e \u003cp\u003e8.5.2 Relationships between Dichotomous Variables 257\u003c\/p\u003e \u003cp\u003e8.6 Conclusion 258\u003c\/p\u003e \u003cp\u003eStatistical Resources for SPSS 259\u003c\/p\u003e \u003cp\u003eReview Questions 267\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Advanced Statistical Analyses 273\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 273\u003c\/p\u003e \u003cp\u003e9.2 Repeated-Measures Analysis of Variance 274\u003c\/p\u003e \u003cp\u003e9.2.1 Capabilities of Repeated-Measures ANOVA 274\u003c\/p\u003e \u003cp\u003e9.2.2 Performing a Repeated-Measures ANOVA 275\u003c\/p\u003e \u003cp\u003e9.3 Multiple Analysis of Variance 278\u003c\/p\u003e \u003cp\u003e9.3.1 Capabilities of MANOVA 279\u003c\/p\u003e \u003cp\u003e9.3.2 Performing a MANOVA 280\u003c\/p\u003e \u003cp\u003e9.4 Analysis of Covariance 282\u003c\/p\u003e \u003cp\u003e9.4.1 Capabilities of ANCOVA 283\u003c\/p\u003e \u003cp\u003e9.4.2 Performing an ANCOVA 284\u003c\/p\u003e \u003cp\u003e9.5 Discriminant Analysis 286\u003c\/p\u003e \u003cp\u003e9.5.1 Capabilities of Discriminant Analysis 287\u003c\/p\u003e \u003cp\u003e9.5.2 Performing a Discriminant Analysis 289\u003c\/p\u003e \u003cp\u003e9.6 Conclusion 290\u003c\/p\u003e \u003cp\u003eStatistical Resources for SPSS 290\u003c\/p\u003e \u003cp\u003eReview Questions 299\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Applying Data 303\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Drawing Conclusions 305\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 305\u003c\/p\u003e \u003cp\u003e10.2 Accepting and Rejecting Hypotheses 306\u003c\/p\u003e \u003cp\u003e10.2.1 The Null Hypothesis–Research Hypothesis Relationship 306\u003c\/p\u003e \u003cp\u003e10.2.2 Matching Null and Research Hypotheses 307\u003c\/p\u003e \u003cp\u003e10.2.3 Different Null and Research Hypotheses 308\u003c\/p\u003e \u003cp\u003e10.3 Drawing Conclusions from Results 310\u003c\/p\u003e \u003cp\u003e10.3.1 Summarizing 311\u003c\/p\u003e \u003cp\u003e10.3.2 Reflecting 313\u003c\/p\u003e \u003cp\u003e10.3.3 Speculating 314\u003c\/p\u003e \u003cp\u003e10.4 Cautions 315\u003c\/p\u003e \u003cp\u003e10.4.1 Alternate Explanations of Causation 316\u003c\/p\u003e \u003cp\u003e10.4.2 High Alpha Values 319\u003c\/p\u003e \u003cp\u003e10.4.3 The Ecological Fallacy 320\u003c\/p\u003e \u003cp\u003e10.4.4 Reductionism 322\u003c\/p\u003e \u003cp\u003e10.5 Conclusion 323\u003c\/p\u003e \u003cp\u003eReview Questions 324\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Writing Research Reports 327\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 327\u003c\/p\u003e \u003cp\u003e11.2 Tone 328\u003c\/p\u003e \u003cp\u003e11.2.1 Language 329\u003c\/p\u003e \u003cp\u003e11.2.2 Presentation of Facts 332\u003c\/p\u003e \u003cp\u003e11.3 Sections of the Research Report 334\u003c\/p\u003e \u003cp\u003e11.3.1 Presentation of Hypothesis 334\u003c\/p\u003e \u003cp\u003eFilling a Gap in Knowledge 335\u003c\/p\u003e \u003cp\u003eBuilding on Past Research 336\u003c\/p\u003e \u003cp\u003eContradicting Past Findings 336\u003c\/p\u003e \u003cp\u003eConnecting Past Findings 338\u003c\/p\u003e \u003cp\u003e11.3.2 Description of Methods 339\u003c\/p\u003e \u003cp\u003eSubjects 339\u003c\/p\u003e \u003cp\u003ePopulation 339\u003c\/p\u003e \u003cp\u003eSampling Methods 340\u003c\/p\u003e \u003cp\u003eMeasures 341\u003c\/p\u003e \u003cp\u003eProcedure 342\u003c\/p\u003e \u003cp\u003e11.3.3 Presentation of Results 344\u003c\/p\u003e \u003cp\u003e11.3.4 Presentation of Conclusions 348\u003c\/p\u003e \u003cp\u003e11.4 Conclusion 348\u003c\/p\u003e \u003cp\u003eReview Questions 348\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendixes 353\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAppendix A: \u003ci\u003eZ\u003c\/i\u003e-Score Table 355\u003c\/p\u003e \u003cp\u003eAppendix B: Table for Critical χ\u003csup\u003e2\u003c\/sup\u003e Values 357\u003c\/p\u003e \u003cp\u003eAppendix C: Table for Critical \u003ci\u003et \u003c\/i\u003eValues 359\u003c\/p\u003e \u003cp\u003eAppendix D: Table for Critical \u003ci\u003eF \u003c\/i\u003eValues 361\u003c\/p\u003e \u003cp\u003eReferences 369\u003c\/p\u003e \u003cp\u003eAnswers to Review Questions 371\u003c\/p\u003e \u003cp\u003eIndex 391\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Mathematics [\u003ca title=\"See our other books on Mathematics\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Mathematics%20%5BPB%5D%22\"\u003ePB\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand 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