{"product_id":"fundamentals-of-statistical-reasoning-in-education-9781118425213","title":"Fundamentals of Statistical Reasoning in","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003ci\u003eFundamentals of Statistical Reasoning in Education 4th Edition\u003c\/i\u003e, like the first three editions, is written largely with students of education in mind. Accordingly, Theodore Coladarci and Casey D. Cobb have drawn primarily on examples and issues found in school settings, such as those having to do with instruction, learning, motivation, and assessment. The emphasis on educational applications notwithstanding, the authors are confident that readers will find \u003ci\u003eFundamentals of Statistical Reasoning in Education 4th Edition\u003c\/i\u003e of general relevance to other disciplines in the behavioral sciences as well.\u003cbr\u003e \u003cbr\u003e The 4th Edition of \u003ci\u003eFundamentals\u003c\/i\u003e is still designed as a one semester book. The authors intentionally sidestep topics that few introductory courses cover (e.g., factorial analysis of variance, repeated measures analysis of variance, multiple regression). At the same time, effect size and confidence intervals are incorporated throughout, which today are regarded \u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"This book, like the first three editions, is written largely with students of education in mind. Accordingly, the authors have drawn primarily on examples and issues found in school settings, such as those having to do with instruction, learning, motivation, and assessment. The emphasis on educational applications notwithstanding, the authors are confident that readers will find this book of general relevance to other disciplines in the behavioral sciences as well.\" (Zentralblatt MATH 2016)\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eChapter 1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Why Statistics? 1\u003c\/p\u003e \u003cp\u003e1.2 Descriptive Statistics 2\u003c\/p\u003e \u003cp\u003e1.3 Inferential Statistics 3\u003c\/p\u003e \u003cp\u003e1.4 The Role of Statistics in Educational Research 4\u003c\/p\u003e \u003cp\u003e1.5 Variables and Their Measurement 5\u003c\/p\u003e \u003cp\u003e1.6 Some Tips on Studying Statistics 8\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART 1 DESCRIPTIVE STATISTICS 13\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Frequency Distributions 14\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Why Organize Data? 14\u003c\/p\u003e \u003cp\u003e2.2 Frequency Distributions for Quantitative Variables 14\u003c\/p\u003e \u003cp\u003e2.3 Grouped Scores 15\u003c\/p\u003e \u003cp\u003e2.4 Some Guidelines for Forming Class Intervals 17\u003c\/p\u003e \u003cp\u003e2.5 Constructing a Grouped-Data Frequency Distribution 18\u003c\/p\u003e \u003cp\u003e2.6 The Relative Frequency Distribution 19\u003c\/p\u003e \u003cp\u003e2.7 Exact Limits 21\u003c\/p\u003e \u003cp\u003e2.8 The Cumulative Percentage Frequency Distribution 22\u003c\/p\u003e \u003cp\u003e2.9 Percentile Ranks 23\u003c\/p\u003e \u003cp\u003e2.10 Frequency Distributions for Qualitative Variables 25\u003c\/p\u003e \u003cp\u003e2.11 Summary 26\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Graphic Representation 34\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Why Graph Data? 34\u003c\/p\u003e \u003cp\u003e3.2 Graphing Qualitative Data: The Bar Chart 34\u003c\/p\u003e \u003cp\u003e3.3 Graphing Quantitative Data: The Histogram 35\u003c\/p\u003e \u003cp\u003e3.4 Relative Frequency and Proportional Area 39\u003c\/p\u003e \u003cp\u003e3.5 Characteristics of Frequency Distributions 41\u003c\/p\u003e \u003cp\u003e3.6 The Box Plot 44\u003c\/p\u003e \u003cp\u003e3.7 Summary 45\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Central Tendency 52\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 The Concept of Central Tendency 52\u003c\/p\u003e \u003cp\u003e4.2 The Mode 52\u003c\/p\u003e \u003cp\u003e4.3 The Median 53\u003c\/p\u003e \u003cp\u003e4.4 The Arithmetic Mean 54\u003c\/p\u003e \u003cp\u003e4.5 Central Tendency and Distribution Symmetry 57\u003c\/p\u003e \u003cp\u003e4.6 Which Measure of Central Tendency to Use? 59\u003c\/p\u003e \u003cp\u003e4.7 Summary 59\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Variability 66\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Central Tendency Is Not Enough: The Importance of Variability 66\u003c\/p\u003e \u003cp\u003e5.2 The Range 67\u003c\/p\u003e \u003cp\u003e5.3 Variability and Deviations From the Mean 68\u003c\/p\u003e \u003cp\u003e5.4 The Variance 69\u003c\/p\u003e \u003cp\u003e5.5 The Standard Deviation 70\u003c\/p\u003e \u003cp\u003e5.6 The Predominance of the Variance and Standard Deviation 71\u003c\/p\u003e \u003cp\u003e5.7 The Standard Deviation and the Normal Distribution 72\u003c\/p\u003e \u003cp\u003e5.8 Comparing Means of Two Distributions: The Relevance of Variability 73\u003c\/p\u003e \u003cp\u003e5.9 In the Denominator: n Versus n −1 75\u003c\/p\u003e \u003cp\u003e5.10 Summary 76\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Normal Distributions and Standard Scores 81\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 A Little History: Sir Francis Galton and the Normal Curve 81\u003c\/p\u003e \u003cp\u003e6.2 Properties of the Normal Curve 82\u003c\/p\u003e \u003cp\u003e6.3 More on the Standard Deviation and the Normal Distribution 82\u003c\/p\u003e \u003cp\u003e6.4 z Scores 84\u003c\/p\u003e \u003cp\u003e6.5 The Normal Curve Table 87\u003c\/p\u003e \u003cp\u003e6.6 Finding Area When the Score Is Known 88\u003c\/p\u003e \u003cp\u003e6.7 Reversing the Process: Finding Scores When the Area Is Known 91\u003c\/p\u003e \u003cp\u003e6.8 Comparing Scores From Different Distributions 93\u003c\/p\u003e \u003cp\u003e6.9 Interpreting Effect Size 94\u003c\/p\u003e \u003cp\u003e6.10 Percentile Ranks and the Normal Distribution 96\u003c\/p\u003e \u003cp\u003e6.11 Other Standard Scores 97\u003c\/p\u003e \u003cp\u003e6.12 Standard Scores Do Not “Normalize” a Distribution 98\u003c\/p\u003e \u003cp\u003e6.13 The Normal Curve and Probability 98\u003c\/p\u003e \u003cp\u003e6.14 Summary 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Correlation 106\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 The Concept of Association 106\u003c\/p\u003e \u003cp\u003e7.2 Bivariate Distributions and Scatterplots 106\u003c\/p\u003e \u003cp\u003e7.3 The Covariance 111\u003c\/p\u003e \u003cp\u003e7.4 The Pearson \u003ci\u003er\u003c\/i\u003e 117\u003c\/p\u003e \u003cp\u003e7.5 Computation of \u003ci\u003er\u003c\/i\u003e: The Calculating Formula 118\u003c\/p\u003e \u003cp\u003e7.6 Correlation and Causation 120\u003c\/p\u003e \u003cp\u003e7.7 Factors Influencing Pearson r 122\u003c\/p\u003e \u003cp\u003e7.8 Judging the Strength of Association: \u003ci\u003er\u003csup\u003e2\u003c\/sup\u003e\u003c\/i\u003e 125\u003c\/p\u003e \u003cp\u003e7.9 Other Correlation Coefficients 127\u003c\/p\u003e \u003cp\u003e7.10 Summary 127\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Regression and Prediction 134\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Correlation Versus Prediction 134\u003c\/p\u003e \u003cp\u003e8.2 Determining the Line of Best Fit 135\u003c\/p\u003e \u003cp\u003e8.3 The Regression Equation in Terms of Raw Scores 138\u003c\/p\u003e \u003cp\u003e8.4 Interpreting the Raw-Score Slope 141\u003c\/p\u003e \u003cp\u003e8.5 The Regression Equation in Terms of z Scores 141\u003c\/p\u003e \u003cp\u003e8.6 Some Insights Regarding Correlation and Prediction 142\u003c\/p\u003e \u003cp\u003e8.7 Regression and Sums of Squares 145\u003c\/p\u003e \u003cp\u003e8.8 Residuals and Unexplained Variation 147\u003c\/p\u003e \u003cp\u003e8.9 Measuring the Margin of Prediction Error: The Standard Error of Estimate 148\u003c\/p\u003e \u003cp\u003e8.10 Correlation and Causality (Revisited) 152\u003c\/p\u003e \u003cp\u003e8.11 Summary 153\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART 2 INFERENTIAL STATISTICS 163\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Probability and Probability Distributions 164\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Statistical Inference: Accounting for Chance in Sample Results 164\u003c\/p\u003e \u003cp\u003e9.2 Probability: The Study of Chance 165\u003c\/p\u003e \u003cp\u003e9.3 Definition of Probability 166\u003c\/p\u003e \u003cp\u003e9.4 Probability Distributions 168\u003c\/p\u003e \u003cp\u003e9.5 The OR\/addition Rule 169\u003c\/p\u003e \u003cp\u003e9.6 The AND\/Multiplication Rule 171\u003c\/p\u003e \u003cp\u003e9.7 The Normal Curve as a Probability Distribution 172\u003c\/p\u003e \u003cp\u003e9.8 “So What?”—Probability Distributions as the Basis for Statistical Inference 174\u003c\/p\u003e \u003cp\u003e9.9 Summary 175\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Sampling Distributions 179\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 From Coins to Means 179\u003c\/p\u003e \u003cp\u003e10.2 Samples and Populations 180\u003c\/p\u003e \u003cp\u003e10.3 Statistics and Parameters 181\u003c\/p\u003e \u003cp\u003e10.4 Random Sampling Model 181\u003c\/p\u003e \u003cp\u003e10.5 Random Sampling in Practice 183\u003c\/p\u003e \u003cp\u003e10.6 Sampling Distributions of Means 184\u003c\/p\u003e \u003cp\u003e10.7 Characteristics of a Sampling Distribution of Means 185\u003c\/p\u003e \u003cp\u003e10.8 Using a Sampling Distribution of Means to Determine Probabilities 188\u003c\/p\u003e \u003cp\u003e10.9 The Importance of Sample Size (n) 191\u003c\/p\u003e \u003cp\u003e10.10 Generality of the Concept of a Sampling Distribution 193\u003c\/p\u003e \u003cp\u003e10.11 Summary 193\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Testing Statistical Hypotheses About μ When σ Is Known: The One-Sample z Test 199\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Testing a Hypothesis About \u003ci\u003eμ\u003c\/i\u003e: Does “Homeschooling” Make a Difference? 199\u003c\/p\u003e \u003cp\u003e11.2 Dr. Meyer’s Problem in a Nutshell 200\u003c\/p\u003e \u003cp\u003e11.3 The Statistical Hypotheses: H\u003csub\u003e0\u003c\/sub\u003e and H\u003csub\u003e1\u003c\/sub\u003e 201\u003c\/p\u003e \u003cp\u003e11.4 The Test Statistic z 202\u003c\/p\u003e \u003cp\u003e11.5 The Probability of the Test Statistic: The \u003ci\u003ep\u003c\/i\u003e Value 203\u003c\/p\u003e \u003cp\u003e11.6 The Decision Criterion: Level of Significance (α) 204\u003c\/p\u003e \u003cp\u003e11.7 The Level of Significance and Decision Error 207\u003c\/p\u003e \u003cp\u003e11.8 The Nature and Role of H\u003csub\u003e0\u003c\/sub\u003e and H\u003csub\u003e1\u003c\/sub\u003e 209\u003c\/p\u003e \u003cp\u003e11.9 Rejection Versus Retention of H\u003csub\u003e0\u003c\/sub\u003e 209\u003c\/p\u003e \u003cp\u003e11.10 Statistical Significance Versus Importance 210\u003c\/p\u003e \u003cp\u003e11.11 Directional and Nondirectional Alternative Hypotheses 212\u003c\/p\u003e \u003cp\u003e11.12 The Substantive Versus the Statistical 214\u003c\/p\u003e \u003cp\u003e11.13 Summary 215\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 Estimation 222\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Hypothesis Testing Versus Estimation 222\u003c\/p\u003e \u003cp\u003e12.2 Point Estimation Versus Interval Estimation 223\u003c\/p\u003e \u003cp\u003e12.3 Constructing an Interval Estimate of \u003ci\u003eμ\u003c\/i\u003e 224\u003c\/p\u003e \u003cp\u003e12.4 Interval Width and Level of Confidence 226\u003c\/p\u003e \u003cp\u003e12.5 Interval Width and Sample Size 227\u003c\/p\u003e \u003cp\u003e12.6 Interval Estimation and Hypothesis Testing 228\u003c\/p\u003e \u003cp\u003e12.7 Advantages of Interval Estimation 230\u003c\/p\u003e \u003cp\u003e12.8 Summary 230\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 Testing Statistical Hypotheses About \u003ci\u003eμ\u003c\/i\u003e When σ Is Not Known: The One-Sample \u003ci\u003et\u003c\/i\u003e Test 235\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Reality: σ Often Is Unknown 235\u003c\/p\u003e \u003cp\u003e13.2 Estimating the Standard Error of the Mean 236\u003c\/p\u003e \u003cp\u003e13.3 The Test Statistic \u003ci\u003et\u003c\/i\u003e 237\u003c\/p\u003e \u003cp\u003e13.4 Degrees of Freedom 238\u003c\/p\u003e \u003cp\u003e13.5 The Sampling Distribution of Student’s \u003ci\u003et\u003c\/i\u003e 239\u003c\/p\u003e \u003cp\u003e13.6 An Application of Student’s \u003ci\u003et\u003c\/i\u003e 242\u003c\/p\u003e \u003cp\u003e13.7 Assumption of Population Normality 244\u003c\/p\u003e \u003cp\u003e13.8 Levels of Significance Versus \u003ci\u003ep\u003c\/i\u003e Values 244\u003c\/p\u003e \u003cp\u003e13.9 Constructing a Confidence Interval for \u003ci\u003eμ\u003c\/i\u003e When σ Is Not Known 246\u003c\/p\u003e \u003cp\u003e13.10 Summary 247\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 Comparing the Means of Two Populations: Independent Samples 253\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 From One Mu (\u003ci\u003eμ\u003c\/i\u003e) to Two 253\u003c\/p\u003e \u003cp\u003e14.2 Statistical Hypotheses 254\u003c\/p\u003e \u003cp\u003e14.3 The Sampling Distribution of Differences Between Means 255\u003c\/p\u003e \u003cp\u003e14.4 Estimating σ\u003csub\u003ex̄\u003csub\u003e1\u003c\/sub\u003e-x̄\u003csub\u003e2\u003c\/sub\u003e \u003c\/sub\u003e 257\u003c\/p\u003e \u003cp\u003e14.5 The \u003ci\u003et\u003c\/i\u003e Test for Two Independent Samples 259\u003c\/p\u003e \u003cp\u003e14.6 Testing Hypotheses About Two Independent Means: An Example 260\u003c\/p\u003e \u003cp\u003e14.7 Interval Estimation of \u003ci\u003eμ\u003csub\u003e1\u003c\/sub\u003e\u003c\/i\u003e − \u003ci\u003eμ\u003csub\u003e2\u003c\/sub\u003e\u003c\/i\u003e 262\u003c\/p\u003e \u003cp\u003e14.8 Appraising the Magnitude of a Difference: Measures of Effect Size for − 264\u003c\/p\u003e \u003cp\u003e14.9 How Were Groups Formed? The Role of Randomization 268\u003c\/p\u003e \u003cp\u003e14.10 Statistical Inferences and Nonstatistical Generalizations 269\u003c\/p\u003e \u003cp\u003e14.11 Summary 270\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15 Comparing the Means of Dependent Samples 278\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 The Meaning of “Dependent” 278\u003c\/p\u003e \u003cp\u003e15.2 Standard Error of the Difference Between Dependent Means 279\u003c\/p\u003e \u003cp\u003e15.3 Degrees of Freedom 281\u003c\/p\u003e \u003cp\u003e15.4 The \u003ci\u003et\u003c\/i\u003e Test for Two Dependent Samples 281\u003c\/p\u003e \u003cp\u003e15.5 Testing Hypotheses About Two Dependent Means: An Example 283\u003c\/p\u003e \u003cp\u003e15.6 Interval Estimation of \u003ci\u003eμ\u003csub\u003eD\u003c\/sub\u003e\u003c\/i\u003e 286\u003c\/p\u003e \u003cp\u003e15.7 Summary 287\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 16 Comparing the Means of Three or More Independent Samples: One-Way Analysis of Variance 294\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Comparing More Than Two Groups: Why Not Multiplet Tests? 294\u003c\/p\u003e \u003cp\u003e16.2 The Statistical Hypotheses in One-Way ANOVA 295\u003c\/p\u003e \u003cp\u003e16.3 The Logic of One-Way ANOVA: An Overview 296\u003c\/p\u003e \u003cp\u003e16.4 Alison’s Reply to Gregory 299\u003c\/p\u003e \u003cp\u003e16.5 Partitioning the Sums of Squares 300\u003c\/p\u003e \u003cp\u003e16.6 Within-Groups and Between- Groups Variance Estimates 303\u003c\/p\u003e \u003cp\u003e16.7 The F Test 304\u003c\/p\u003e \u003cp\u003e16.8 Tukey’s “HSD” Test 306\u003c\/p\u003e \u003cp\u003e16.9 Interval Estimation of \u003ci\u003eμ\u003csub\u003ei\u003c\/sub\u003e − μ\u003csub\u003ej\u003c\/sub\u003e\u003c\/i\u003e 308\u003c\/p\u003e \u003cp\u003e16.10 One-Way ANOVA: Summarizing the Steps 309\u003c\/p\u003e \u003cp\u003e16.11 Estimating the Strength of the Treatment Effect: Effect Size (ω\u003csup\u003e2\u003c\/sup\u003e) 311\u003c\/p\u003e \u003cp\u003e16.12 ANOVA Assumptions (and Other Considerations) 312\u003c\/p\u003e \u003cp\u003e16.13 Summary 313\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 17 Inferences about the Pearson Correlation Coefficient 322\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 From \u003ci\u003eμ\u003c\/i\u003e to \u003ci\u003eρ\u003c\/i\u003e 322\u003c\/p\u003e \u003cp\u003e17.2 The Sampling Distribution of \u003ci\u003er\u003c\/i\u003e When \u003ci\u003eρ\u003c\/i\u003e = 0 322\u003c\/p\u003e \u003cp\u003e17.3 Testing the Statistical Hypothesis That \u003ci\u003eρ\u003c\/i\u003e = 0 324\u003c\/p\u003e \u003cp\u003e17.4 An Example 324\u003c\/p\u003e \u003cp\u003e17.5 In Brief: Student’s t Distribution and the Regression Slope (\u003ci\u003eb\u003c\/i\u003e) 326\u003c\/p\u003e \u003cp\u003e17.6 Table E 326\u003c\/p\u003e \u003cp\u003e17.7 The Role of n in the Statistical Significance of \u003ci\u003er\u003c\/i\u003e 328\u003c\/p\u003e \u003cp\u003e17.8 Statistical Significance Versus Importance (Again) 329\u003c\/p\u003e \u003cp\u003e17.9 Testing Hypotheses Other Than \u003ci\u003eρ\u003c\/i\u003e = 0 329\u003c\/p\u003e \u003cp\u003e17.10 Interval Estimation of \u003ci\u003eρ\u003c\/i\u003e 330\u003c\/p\u003e \u003cp\u003e17.11 Summary 332\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 18 Making Inferences From Frequency Data 338\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Frequency Data Versus Score Data 338\u003c\/p\u003e \u003cp\u003e18.2 A Problem Involving Frequencies: The One-Variable Case 339\u003c\/p\u003e \u003cp\u003e18.3 χ\u003csup\u003e2\u003c\/sup\u003e: A Measure of Discrepancy Between Expected and Observed Frequencies 340\u003c\/p\u003e \u003cp\u003e18.4 The Sampling Distribution of χ\u003csup\u003e2\u003c\/sup\u003e 341\u003c\/p\u003e \u003cp\u003e18.5 Completion of the Voter Survey Problem: The χ\u003csup\u003e2\u003c\/sup\u003e Goodness-of-Fit Test 343\u003c\/p\u003e \u003cp\u003e18.6 The χ\u003csup\u003e2\u003c\/sup\u003e Test of a Single Proportion 344\u003c\/p\u003e \u003cp\u003e18.7 Interval Estimate of a Single Proportion 345\u003c\/p\u003e \u003cp\u003e18.8 When There Are Two Variables: The χ\u003csup\u003e2\u003c\/sup\u003e Test of Independence 347\u003c\/p\u003e \u003cp\u003e18.9 Finding Expected Frequencies in the Two-Variable Case 348\u003c\/p\u003e \u003cp\u003e18.10 Calculating the Two-Variable χ\u003csup\u003e2\u003c\/sup\u003e 350\u003c\/p\u003e \u003cp\u003e18.11 The χ\u003csup\u003e2\u003c\/sup\u003e Test of Independence: Summarizing the Steps 351\u003c\/p\u003e \u003cp\u003e18.12 The 2 × 2 Contingency Table 352\u003c\/p\u003e \u003cp\u003e18.13 Testing a Difference Between Two Proportions 353\u003c\/p\u003e \u003cp\u003e18.14 The Independence of Observations 353\u003c\/p\u003e \u003cp\u003e18.15 χ2 and Quantitative Variables 354\u003c\/p\u003e \u003cp\u003e18.16 Other Considerations 355\u003c\/p\u003e \u003cp\u003e18.17 Summary 355\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 19 Statistical “Power” (and How to Increase It) 363\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e19.1 The Power of a Statistical Test 363\u003c\/p\u003e \u003cp\u003e19.2 Power and Type II Error 364\u003c\/p\u003e \u003cp\u003e19.3 Effect Size (Revisited) 365\u003c\/p\u003e \u003cp\u003e19.4 Factors Affecting Power: The Effect Size 366\u003c\/p\u003e \u003cp\u003e19.5 Factors Affecting Power: Sample Size 367\u003c\/p\u003e \u003cp\u003e19.6 Additional Factors Affecting Power 368\u003c\/p\u003e \u003cp\u003e19.7 Significance Versus Importance 369\u003c\/p\u003e \u003cp\u003e19.8 Selecting an Appropriate Sample Size 370\u003c\/p\u003e \u003cp\u003e19.9 Summary 373 Epilogue A Note on (Almost) Assumption-Free Tests 379\u003c\/p\u003e \u003cp\u003eReferences 380\u003c\/p\u003e \u003cp\u003eAppendix A Review of Basic Mathematics 382\u003c\/p\u003e \u003cp\u003eA.1 Introduction 382\u003c\/p\u003e \u003cp\u003eA.2 Symbols and Their Meaning 382\u003c\/p\u003e \u003cp\u003eA.3 Arithmetic Operations Involving Positive and Negative Numbers 383\u003c\/p\u003e \u003cp\u003eA.4 Squares and Square Roots 383\u003c\/p\u003e \u003cp\u003eA.5 Fractions 384\u003c\/p\u003e \u003cp\u003eA.6 Operations Involving Parentheses 385\u003c\/p\u003e \u003cp\u003eA.7 Approximate Numbers, Computational Accuracy, and Rounding 386\u003c\/p\u003e \u003cp\u003eAppendix B Answers to Selected End-of-Chapter Problems 387\u003c\/p\u003e \u003cp\u003eAppendix C Statistical Tables 408\u003c\/p\u003e \u003cp\u003eGlossary 421\u003c\/p\u003e \u003cp\u003eIndex 427\u003c\/p\u003e \u003cp\u003eUseful Formulas 433\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49528828756311,"sku":"9781118425213","price":72.86,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118425213.jpg?v=1731873179","url":"https:\/\/bookcurl.com\/products\/fundamentals-of-statistical-reasoning-in-education-9781118425213","provider":"Book 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