{"product_id":"using-statistics-in-the-social-and-health-sciences-with-spss-and-excel-isbn-9781119121046","title":"Using Statistics in the Social and Health Sciences with SPSS and Excel","description":"\u003cp\u003e\u003cb\u003eProvides a step-by-step approach to statistical procedures to analyze data and conduct research, with detailed sections in each chapter explaining SPSS® and Excel® applications\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThis book identifies connections between statistical applications and research design using cases, examples, and discussion of specific topics from the social and health sciences. Researched and class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations for both the novice and professional alike to understand the fundamental statistical practices for organizing, analyzing, and drawing conclusions from research data in their field.\u003c\/p\u003e \u003cp\u003eThe book begins with an introduction to descriptive and inferential statistics and then acquaints readers with important features of statistical applications (SPSS and Excel) that support statistical analysis and decision making. Subsequent chapters treat the procedures commonly employed when working with data across various fields of social science research. Individual chapters are devoted to specific statistical procedures, each ending with lab application exercises that pose research questions, examine the questions through their application in SPSS and Excel, and conclude with a brief research report that outlines key findings drawn from the results. Real-world examples and data from social and health sciences research are used throughout the book, allowing readers to reinforce their comprehension of the material.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eUsing Statistics in the Social and Health Sciences with SPSS® and Excel® \u003c\/i\u003eincludes:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eUse of straightforward procedures and examples that help students focus on understanding of analysis and interpretation of findings\u003c\/li\u003e \u003cli\u003eInclusion of a data lab section in each chapter that provides relevant, clear examples\u003c\/li\u003e \u003cli\u003eIntroduction to advanced statistical procedures in chapter sections (e.g., regression diagnostics) and separate chapters (e.g., multiple linear regression) for greater relevance to real-world research needs\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eEmphasizing applied statistical analyses, this book can serve as the primary text in undergraduate and graduate university courses within departments of sociology, psychology, urban studies, health sciences, and public health, as well as other related departments. It will also be useful to statistics practitioners through extended sections using SPSS® and Excel® for analyzing data.\u003c\/p\u003e \u003cp\u003ePreface xv\u003c\/p\u003e \u003cp\u003eAcknowledgments xix\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBig Data Analysis 1\u003c\/p\u003e \u003cp\u003eVisual Data Analysis 2\u003c\/p\u003e \u003cp\u003eImportance of Statistics for the Social and Health Sciences and Medicine 3\u003c\/p\u003e \u003cp\u003eHistorical Notes: Early Use of Statistics 4\u003c\/p\u003e \u003cp\u003eApproach of the Book 6\u003c\/p\u003e \u003cp\u003eCases from Current Research 7\u003c\/p\u003e \u003cp\u003eResearch Design 9\u003c\/p\u003e \u003cp\u003eFocus on Interpretation 9\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Descriptive Statistics: Central Tendency 13\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat is the Whole Truth? Research Applications (Spuriousness) 13\u003c\/p\u003e \u003cp\u003eDescriptive and Inferential Statistics 16\u003c\/p\u003e \u003cp\u003eThe Nature of Data: Scales of Measurement 16\u003c\/p\u003e \u003cp\u003eDescriptive Statistics: Central Tendency 23\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e and Excel to Understand Central Tendency 28\u003c\/p\u003e \u003cp\u003eDistributions 35\u003c\/p\u003e \u003cp\u003eDescribing the Normal Distribution: Numerical Methods 37\u003c\/p\u003e \u003cp\u003eDescriptive Statistics: Using Graphical Methods 41\u003c\/p\u003e \u003cp\u003eTerms and Concepts 47\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 49\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 51\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Descriptive Statistics: Variability 55\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eRange 55\u003c\/p\u003e \u003cp\u003ePercentile 56\u003c\/p\u003e \u003cp\u003eScores Based on Percentiles 57\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e and Excel to Identify Percentiles 57\u003c\/p\u003e \u003cp\u003eStandard Deviation and Variance 60\u003c\/p\u003e \u003cp\u003eCalculating the Variance and Standard Deviation 61\u003c\/p\u003e \u003cp\u003ePopulation SD and Inferential SD 66\u003c\/p\u003e \u003cp\u003eObtaining SD from Excel and SPSS\u003csup\u003e®\u003c\/sup\u003e 67\u003c\/p\u003e \u003cp\u003eTerms and Concepts 70\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 71\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 73\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 The Normal Distribution 77\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Nature of the Normal Curve 77\u003c\/p\u003e \u003cp\u003eThe Standard Normal Score: \u003ci\u003eZ Score\u003c\/i\u003e 79\u003c\/p\u003e \u003cp\u003eThe \u003ci\u003eZ \u003c\/i\u003eScore Table of Values 80\u003c\/p\u003e \u003cp\u003eNavigating the \u003ci\u003eZ \u003c\/i\u003eScore Distribution 81\u003c\/p\u003e \u003cp\u003eCalculating Percentiles 83\u003c\/p\u003e \u003cp\u003eCreating Rules for Locating \u003ci\u003eZ \u003c\/i\u003eScores 84\u003c\/p\u003e \u003cp\u003eCalculating \u003ci\u003eZ \u003c\/i\u003eScores 87\u003c\/p\u003e \u003cp\u003eWorking with Raw Score Distributions 90\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e to Create \u003ci\u003eZ \u003c\/i\u003eScores and Percentiles 90\u003c\/p\u003e \u003cp\u003eUsing Excel to Create \u003ci\u003eZ \u003c\/i\u003eScores 94\u003c\/p\u003e \u003cp\u003eUsing Excel and SPSS\u003csup\u003e®\u003c\/sup\u003e for Distribution Descriptions 97\u003c\/p\u003e \u003cp\u003eTerms and Concepts 99\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 99\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 101\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Probability and the \u003ci\u003eZ \u003c\/i\u003eDistribution 105\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Nature of Probability 106\u003c\/p\u003e \u003cp\u003eElements of Probability 106\u003c\/p\u003e \u003cp\u003eCombinations and Permutations 109\u003c\/p\u003e \u003cp\u003eConditional Probability: Using Bayes’ Theorem 111\u003c\/p\u003e \u003cp\u003e\u003ci\u003eZ \u003c\/i\u003eScore Distribution and Probability 112\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e and Excel to Transform Scores 117\u003c\/p\u003e \u003cp\u003eUsing the Attributes of the Normal Curve to Calculate Probability 119\u003c\/p\u003e \u003cp\u003e“Exact” Probability 123\u003c\/p\u003e \u003cp\u003eFrom Sample Values to Sample Distributions 126\u003c\/p\u003e \u003cp\u003eTerms and Concepts 127\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 128\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 129\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Research Design and Inferential Statistics 133\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eResearch Design 133\u003c\/p\u003e \u003cp\u003eExperiment 136\u003c\/p\u003e \u003cp\u003eNon-Experimental or Post Facto Research Designs 140\u003c\/p\u003e \u003cp\u003eInferential Statistics 143\u003c\/p\u003e \u003cp\u003e\u003ci\u003eZ \u003c\/i\u003eTest 154\u003c\/p\u003e \u003cp\u003eThe Hypothesis Test 154\u003c\/p\u003e \u003cp\u003eStatistical Significance 156\u003c\/p\u003e \u003cp\u003ePractical Significance: Effect Size 156\u003c\/p\u003e \u003cp\u003e\u003ci\u003eZ \u003c\/i\u003eTest Elements 156\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e and Excel for the \u003ci\u003eZ \u003c\/i\u003eTest 157\u003c\/p\u003e \u003cp\u003eTerms and Concepts 158\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 161\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 162\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 The \u003ci\u003eT \u003c\/i\u003eTest for Single Samples 165\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction 166\u003c\/p\u003e \u003cp\u003e\u003ci\u003eZ \u003c\/i\u003eVersus \u003ci\u003eT\u003c\/i\u003e: Making Accommodations 166\u003c\/p\u003e \u003cp\u003eResearch Design 167\u003c\/p\u003e \u003cp\u003eParameter Estimation 169\u003c\/p\u003e \u003cp\u003eThe \u003ci\u003eT \u003c\/i\u003eTest 173\u003c\/p\u003e \u003cp\u003eThe \u003ci\u003eT \u003c\/i\u003eTest: A Research Example 176\u003c\/p\u003e \u003cp\u003eInterpreting the Results of the \u003ci\u003eT \u003c\/i\u003eTest for a Single Mean 180\u003c\/p\u003e \u003cp\u003eThe \u003ci\u003eT \u003c\/i\u003eDistribution 181\u003c\/p\u003e \u003cp\u003eThe Hypothesis Test for the Single Sample \u003ci\u003eT \u003c\/i\u003eTest 182\u003c\/p\u003e \u003cp\u003eType I and Type II Errors 183\u003c\/p\u003e \u003cp\u003eEffect Size 187\u003c\/p\u003e \u003cp\u003eEffect Size for the Single Sample \u003ci\u003eT \u003c\/i\u003eTest 187\u003c\/p\u003e \u003cp\u003ePower Effect Size and Beta 188\u003c\/p\u003e \u003cp\u003eOne- and Two-Tailed Tests 189\u003c\/p\u003e \u003cp\u003ePoint and Interval Estimates 192\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e and Excel with the Single Sample \u003ci\u003eT \u003c\/i\u003eTest 196\u003c\/p\u003e \u003cp\u003eTerms and Concepts 201\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 201\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 203\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Independent Sample \u003ci\u003eT \u003c\/i\u003eTest 207\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA Lot of “Ts” 207\u003c\/p\u003e \u003cp\u003eResearch Design 208\u003c\/p\u003e \u003cp\u003eExperimental Designs and the Independent \u003ci\u003eT \u003c\/i\u003eTest 208\u003c\/p\u003e \u003cp\u003eDependent Sample Designs 209\u003c\/p\u003e \u003cp\u003eBetween and Within Research Designs 210\u003c\/p\u003e \u003cp\u003eUsing Different \u003ci\u003eT \u003c\/i\u003eTests 211\u003c\/p\u003e \u003cp\u003eIndependent \u003ci\u003eT \u003c\/i\u003eTest: The Procedure 213\u003c\/p\u003e \u003cp\u003eCreating the Sampling Distribution of Differences 215\u003c\/p\u003e \u003cp\u003eThe Nature of the Sampling Distribution of Differences 216\u003c\/p\u003e \u003cp\u003eCalculating the Estimated Standard Error of Difference with Equal Sample Size 218\u003c\/p\u003e \u003cp\u003eUsing Unequal Sample Sizes 219\u003c\/p\u003e \u003cp\u003eThe Independent \u003ci\u003eT \u003c\/i\u003eRatio 221\u003c\/p\u003e \u003cp\u003eIndependent \u003ci\u003eT \u003c\/i\u003eTest Example 222\u003c\/p\u003e \u003cp\u003eHypothesis Test Elements for the Example 222\u003c\/p\u003e \u003cp\u003eBefore–After Convention with the Independent \u003ci\u003eT \u003c\/i\u003eTest 226\u003c\/p\u003e \u003cp\u003eConfidence Intervals for the Independent \u003ci\u003eT \u003c\/i\u003eTest 227\u003c\/p\u003e \u003cp\u003eEffect Size 228\u003c\/p\u003e \u003cp\u003eThe Assumptions for the Independent \u003ci\u003eT \u003c\/i\u003eTest 230\u003c\/p\u003e \u003cp\u003eSPSS\u003csup\u003e®\u003c\/sup\u003e Explore for Checking the Normal Distribution Assumption 231\u003c\/p\u003e \u003cp\u003eExcel Procedures for Checking the Equal Variance Assumption 233\u003c\/p\u003e \u003cp\u003eSPSS\u003csup\u003e®\u003c\/sup\u003e Procedure for Checking the Equal Variance Assumption 237\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e and Excel with the Independent \u003ci\u003eT \u003c\/i\u003eTest 239\u003c\/p\u003e \u003cp\u003eSPSS\u003csup\u003e® \u003c\/sup\u003eProcedures for the Independent \u003ci\u003eT \u003c\/i\u003eTest 239\u003c\/p\u003e \u003cp\u003eExcel Procedures for the Independent \u003ci\u003eT \u003c\/i\u003eTest 243\u003c\/p\u003e \u003cp\u003eEffect Size for the Independent \u003ci\u003eT \u003c\/i\u003eTest Example 245\u003c\/p\u003e \u003cp\u003eParting Comments 245\u003c\/p\u003e \u003cp\u003eNonparametric Statistics: The Mann–Whitney \u003ci\u003eU \u003c\/i\u003eTest 246\u003c\/p\u003e \u003cp\u003eTerms and Concepts 249\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 249\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 251\u003c\/p\u003e \u003cp\u003eGraphics in the Data Summary 254\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Analysis of Variance 255\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA Hypothetical Example of ANOVA 255\u003c\/p\u003e \u003cp\u003eThe Nature of ANOVA 257\u003c\/p\u003e \u003cp\u003eThe Components of Variance 258\u003c\/p\u003e \u003cp\u003eThe Process of ANOVA 259\u003c\/p\u003e \u003cp\u003eCalculating ANOVA 260\u003c\/p\u003e \u003cp\u003eEffect Size 268\u003c\/p\u003e \u003cp\u003ePost Hoc Analyses 269\u003c\/p\u003e \u003cp\u003eAssumptions of ANOVA 274\u003c\/p\u003e \u003cp\u003eAdditional Considerations with ANOVA 275\u003c\/p\u003e \u003cp\u003eThe Hypothesis Test: Interpreting ANOVA Results 276\u003c\/p\u003e \u003cp\u003eAre the Assumptions Met? 276\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e and Excel with One-Way ANOVA 282\u003c\/p\u003e \u003cp\u003eThe Need for Diagnostics 289\u003c\/p\u003e \u003cp\u003eNon-Parametric ANOVA Tests: The Kruskal–Wallis Test 289\u003c\/p\u003e \u003cp\u003eTerms and Concepts 292\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 293\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 294\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Factorial ANOVA 297\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eExtensions of ANOVA 297\u003c\/p\u003e \u003cp\u003eANCOVA 298\u003c\/p\u003e \u003cp\u003eMANOVA 299\u003c\/p\u003e \u003cp\u003eMANCOVA 299\u003c\/p\u003e \u003cp\u003eFactorial ANOVA 299\u003c\/p\u003e \u003cp\u003eInteraction Effects 299\u003c\/p\u003e \u003cp\u003eSimple Effects 301\u003c\/p\u003e \u003cp\u003e2XANOVA: An Example 302\u003c\/p\u003e \u003cp\u003eCalculating Factorial ANOVA 303\u003c\/p\u003e \u003cp\u003eThe Hypotheses Test: Interpreting Factorial ANOVA Results 306\u003c\/p\u003e \u003cp\u003eEffect Size for 2XANOVA: Partial 𝜂\u003csup\u003e2\u003c\/sup\u003e 308\u003c\/p\u003e \u003cp\u003eDiscussing the Results 309\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e® \u003c\/sup\u003eto Analyze 2XANOVA 311\u003c\/p\u003e \u003cp\u003eSummary Chart for 2XANOVA Procedures 319\u003c\/p\u003e \u003cp\u003eTerms and Concepts 319\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 320\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 320\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Correlation 329\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Nature of Correlation 330\u003c\/p\u003e \u003cp\u003eThe Correlation Design 331\u003c\/p\u003e \u003cp\u003ePearson’s Correlation Coefficient 332\u003c\/p\u003e \u003cp\u003ePlotting the Correlation: The Scattergram 334\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e to Create Scattergrams 337\u003c\/p\u003e \u003cp\u003eUsing Excel to Create Scattergrams 339\u003c\/p\u003e \u003cp\u003eCalculating Pearson’s \u003ci\u003er\u003c\/i\u003e 341\u003c\/p\u003e \u003cp\u003eThe \u003ci\u003eZ \u003c\/i\u003eScore Method 342\u003c\/p\u003e \u003cp\u003eThe Computation Method 344\u003c\/p\u003e \u003cp\u003eThe Hypothesis Test for Pearson’s \u003ci\u003er\u003c\/i\u003e 345\u003c\/p\u003e \u003cp\u003eEffect Size: the Coefficient of Determination 347\u003c\/p\u003e \u003cp\u003eDiagnostics: Correlation Problems 349\u003c\/p\u003e \u003cp\u003eCorrelation Using SPSS\u003csup\u003e®\u003c\/sup\u003e and Excel 352\u003c\/p\u003e \u003cp\u003eNonparametric Statistics: Spearman’s Rank Order Correlation (\u003ci\u003er\u003csub\u003es\u003c\/sub\u003e\u003c\/i\u003e) 358\u003c\/p\u003e \u003cp\u003eTerms and Concepts 363\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 364\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 365\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Bivariate Regression 371\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Nature of Regression 372\u003c\/p\u003e \u003cp\u003eThe Regression Line 374\u003c\/p\u003e \u003cp\u003eCalculating Regression 376\u003c\/p\u003e \u003cp\u003eEffect Size of Regression 379\u003c\/p\u003e \u003cp\u003eThe \u003ci\u003eZ \u003c\/i\u003eScore Formula for Regression 380\u003c\/p\u003e \u003cp\u003eTesting the Regression Hypotheses 382\u003c\/p\u003e \u003cp\u003eThe Standard Error of Estimate 383\u003c\/p\u003e \u003cp\u003eConfidence Interval 385\u003c\/p\u003e \u003cp\u003eExplaining Variance Through Regression 386\u003c\/p\u003e \u003cp\u003eA Numerical Example of Partitioning the Variation 389\u003c\/p\u003e \u003cp\u003eUsing Excel and SPSS\u003csup\u003e®\u003c\/sup\u003e with Bivariate Regression 390\u003c\/p\u003e \u003cp\u003eThe SPSS\u003csup\u003e®\u003c\/sup\u003e Regression Output 390\u003c\/p\u003e \u003cp\u003eThe Excel Regression Output 396\u003c\/p\u003e \u003cp\u003eComplete Example of Bivariate Linear Regression 398\u003c\/p\u003e \u003cp\u003eAssumptions of Bivariate Regression 398\u003c\/p\u003e \u003cp\u003eThe Omnibus Test Results 404\u003c\/p\u003e \u003cp\u003eEffect Size 404\u003c\/p\u003e \u003cp\u003eThe Model Summary 405\u003c\/p\u003e \u003cp\u003eThe Regression Equation and Individual Predictor Test of Significance 405\u003c\/p\u003e \u003cp\u003eAdvanced Regression Procedures 406\u003c\/p\u003e \u003cp\u003eDetecting Problems in Bivariate Linear Regression 408\u003c\/p\u003e \u003cp\u003eTerms and Concepts 409\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 410\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 411\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Introduction to Multiple Linear Regression 417\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Elements of Multiple Linear Regression 417\u003c\/p\u003e \u003cp\u003eSame Process as Bivariate Regression 418\u003c\/p\u003e \u003cp\u003eSome Differences between Bivariate Linear Regression and Multiple Linear Regression 419\u003c\/p\u003e \u003cp\u003eStuff not Covered 420\u003c\/p\u003e \u003cp\u003eAssumptions of Multiple Linear Regression 421\u003c\/p\u003e \u003cp\u003eAnalyzing Residuals to Check MLR Assumptions 422\u003c\/p\u003e \u003cp\u003eDiagnostics for MLR: Cleaning and Checking Data 423\u003c\/p\u003e \u003cp\u003eExtreme Scores 424\u003c\/p\u003e \u003cp\u003eDistance Statistics 428\u003c\/p\u003e \u003cp\u003eInfluence Statistics 429\u003c\/p\u003e \u003cp\u003eMLR Extended Example Data 430\u003c\/p\u003e \u003cp\u003eAssumptions Met? 431\u003c\/p\u003e \u003cp\u003eAnalyzing Residuals: Are Assumptions Met? 433\u003c\/p\u003e \u003cp\u003eInterpreting the SPSS\u003csup\u003e®\u003c\/sup\u003e Findings for MLR 436\u003c\/p\u003e \u003cp\u003eEntering Predictors Together as a Block 437\u003c\/p\u003e \u003cp\u003eEntering Predictors Separately 442\u003c\/p\u003e \u003cp\u003eAdditional Entry Methods for MLR Analyses 447\u003c\/p\u003e \u003cp\u003eExample Study Conclusion 448\u003c\/p\u003e \u003cp\u003eTerms and Concepts 448\u003c\/p\u003e \u003cp\u003eData Lab and Example (with Solution) 450\u003c\/p\u003e \u003cp\u003eData Lab: Solution 450\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Chi-Square and Contingency Table Analysis 455\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eContingency Tables 455\u003c\/p\u003e \u003cp\u003eThe Chi-square Procedure and Research Design 456\u003c\/p\u003e \u003cp\u003eChi-square Design One: Goodness of Fit 457\u003c\/p\u003e \u003cp\u003eA Hypothetical Example: Goodness of Fit 458\u003c\/p\u003e \u003cp\u003eEffect Size: Goodness of Fit 462\u003c\/p\u003e \u003cp\u003eChi-square Design Two: The Test of Independence 463\u003c\/p\u003e \u003cp\u003eA Hypothetical Example: Test of Independence 464\u003c\/p\u003e \u003cp\u003eSpecial 2 × 2 Chi-square 468\u003c\/p\u003e \u003cp\u003eEffect Size in 2 × 2 Tables: PHI 470\u003c\/p\u003e \u003cp\u003eCramer’s \u003ci\u003eV\u003c\/i\u003e: Effect Size for the Chi-square Test of Independence 471\u003c\/p\u003e \u003cp\u003eRepeated Measures Chi-square: Mcnemar Test 472\u003c\/p\u003e \u003cp\u003eUsing SPSS® and Excel with Chi-square 474\u003c\/p\u003e \u003cp\u003eUsing SPSS® for the Chi-square Test of Independence 475\u003c\/p\u003e \u003cp\u003eUsing Excel for Chi-square Analyses 481\u003c\/p\u003e \u003cp\u003eTerms and Concepts 483\u003c\/p\u003e \u003cp\u003eData Lab and Examples (with Solutions) 483\u003c\/p\u003e \u003cp\u003eData Lab: Solutions 484\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Repeated Measures Procedures: \u003ci\u003eT\u003c\/i\u003e\u003c\/b\u003e\u003csub\u003edep\u003c\/sub\u003e \u003cb\u003eand ANOVA\u003c\/b\u003e\u003csub\u003eWS\u003c\/sub\u003e \u003cb\u003e489\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIndependent and Dependent Samples in Research Designs 490\u003c\/p\u003e \u003cp\u003eUsing Different \u003ci\u003eT \u003c\/i\u003eTests 491\u003c\/p\u003e \u003cp\u003eThe Dependent \u003ci\u003eT \u003c\/i\u003eTest Calculation: The “Long” Formula 491\u003c\/p\u003e \u003cp\u003eExample: The Long Formula 492\u003c\/p\u003e \u003cp\u003eThe Dependent \u003ci\u003eT \u003c\/i\u003eTest Calculation: The “Difference” Formula 494\u003c\/p\u003e \u003cp\u003e\u003ci\u003eT\u003c\/i\u003e\u003csub\u003edep\u003c\/sub\u003e and Power 496\u003c\/p\u003e \u003cp\u003eConducting The \u003ci\u003eT\u003c\/i\u003e\u003csub\u003edep\u003c\/sub\u003e Analysis Using SPSS\u003csup\u003e®\u003c\/sup\u003e 496\u003c\/p\u003e \u003cp\u003eConducting The \u003ci\u003eT\u003c\/i\u003e\u003csub\u003edep\u003c\/sub\u003e Analysis Using Excel 498      \u003c\/p\u003e \u003cp\u003eWithin-Subject ANOVA (ANOVA\u003csub\u003eWS\u003c\/sub\u003e) 498\u003c\/p\u003e \u003cp\u003eExperimental Designs 499\u003c\/p\u003e \u003cp\u003ePost Facto Designs 500\u003c\/p\u003e \u003cp\u003eWithin-Subject Example 501\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e®\u003c\/sup\u003e for Within-Subject Data 501\u003c\/p\u003e \u003cp\u003eThe SPSS\u003csup\u003e®\u003c\/sup\u003e Procedure 502\u003c\/p\u003e \u003cp\u003eThe SPSS\u003csup\u003e®\u003c\/sup\u003e Output 504\u003c\/p\u003e \u003cp\u003eNonparametric Statistics 508\u003c\/p\u003e \u003cp\u003eTerms and Concepts 508\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendices\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix A SPSS\u003csup\u003e®\u003c\/sup\u003e Basics 509\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eUsing SPSS\u003csup\u003e® \u003c\/sup\u003e509\u003c\/p\u003e \u003cp\u003eGeneral Features 510\u003c\/p\u003e \u003cp\u003eManagement Functions 513\u003c\/p\u003e \u003cp\u003eAdditional Management Functions 517\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix B Excel Basics 531\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eData Management 531\u003c\/p\u003e \u003cp\u003eThe Excel Menus 533\u003c\/p\u003e \u003cp\u003eUsing Statistical Functions 541\u003c\/p\u003e \u003cp\u003eData Analysis Procedures 543\u003c\/p\u003e \u003cp\u003eMissing Values and “0” Values in Excel Analyses 544\u003c\/p\u003e \u003cp\u003eUsing Excel with “Real Data” 544\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix C Statistical Tables 545\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTable C.1: \u003ci\u003eZ\u003c\/i\u003e-Score Table (Values Shown are Percentages – %) 545\u003c\/p\u003e \u003cp\u003eTable C.2: Exclusion Values for the \u003ci\u003eT\u003c\/i\u003e-Distribution 547\u003c\/p\u003e \u003cp\u003eTable C.3: Critical (Exclusion) Values for the Distribution of \u003ci\u003eF\u003c\/i\u003e 548\u003c\/p\u003e \u003cp\u003eTable C.4: Tukey’s Range Test (Upper 5% Points) 551\u003c\/p\u003e \u003cp\u003eTable C.5: Critical (Exclusion) Values for Pearson’s Correlation Coefficient \u003ci\u003er\u003c\/i\u003e 552\u003c\/p\u003e \u003cp\u003eTable C.6: Critical Values of the \u003ci\u003e𝜒\u003c\/i\u003e\u003csup\u003e2\u003c\/sup\u003e (Chi-Square) Distribution 553\u003c\/p\u003e \u003cp\u003eReferences 555\u003c\/p\u003e \u003cp\u003eIndex 557\u003c\/p\u003e \u003cb\u003eMartin Lee Abbott, PhD,\u003c\/b\u003e is Professor of Sociology at Seattle Pacific University, where he has served as Executive Director of the Washington School Research Center, an independent research and data analysis center funded by the Bill \u0026amp; Melinda Gates Foundation. Dr. Abbott has held positions in both academia and industry, focusing his consulting and teaching in the areas of statistical procedures, program evaluation, applied sociology, and research methods. He is the author of \u003ci\u003eUnderstanding Educational Statistics Using Microsoft Excel\u003c\/i\u003e and \u003ci\u003eSPSS, The Program Evaluation Prism: Using Statistical Methods to Discover Patterns\u003c\/i\u003e, and \u003ci\u003eUnderstanding and Applying Research Design\u003c\/i\u003e, also from Wiley. \u003cp\u003e\u003cb\u003eProvides a step-by-step approach to statistical procedures to analyze data and conduct research, with detailed sections in each chapter explaining SPSS® and Excel® applications\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThis book identifies connections between statistical applications and research design using cases, examples, and discussion of specific topics from the social and health sciences. Researched and class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations for both the novice and professional alike to understand the fundamental statistical practices for organizing, analyzing, and drawing conclusions from research data in their field.\u003c\/p\u003e \u003cp\u003eThe book begins with an introduction to descriptive and inferential statistics and then acquaints readers with important features of statistical applications (SPSS and Excel) that support statistical analysis and decision making. Subsequent chapters treat the procedures commonly employed when working with data across various fields of social science research. Individual chapters are devoted to specific statistical procedures, each ending with lab application exercises that pose research questions, examine the questions through their application in SPSS and Excel, and conclude with a brief research report that outlines key findings drawn from the results. Real-world examples and data from social and health sciences research are used throughout the book, allowing readers to reinforce their comprehension of the material.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eUsing Statistics in the Social and Health Sciences with SPSS® and Excel® \u003c\/i\u003eincludes:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eUse of straightforward procedures and examples that help students focus on understanding of analysis and interpretation of findings\u003c\/li\u003e \u003cli\u003eInclusion of a data lab section in each chapter that provides relevant, clear examples\u003c\/li\u003e \u003cli\u003eIntroduction to advanced statistical procedures in chapter sections (e.g., regression diagnostics) and separate chapters (e.g., multiple linear regression) for greater relevance to real-world research needs\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eEmphasizing applied statistical analyses, this book can serve as the primary text in undergraduate and graduate university courses within departments of sociology, psychology, urban studies, health sciences, and public health, as well as other related departments. It will also be useful to statistics practitioners through extended sections using SPSS® and Excel® for analyzing data.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47990443016421,"sku":"NP9781119121046","price":133.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119121046.jpg?v=1761787849","url":"https:\/\/k12savings.com\/products\/using-statistics-in-the-social-and-health-sciences-with-spss-and-excel-isbn-9781119121046","provider":"K12savings","version":"1.0","type":"link"}