Statistics Unplugged, 3rd Edition

Learn statistics the easy way with STATISTICS UNPLUGGED! Easy-to-understand and student-friendly, this practical text takes the intimidation out of statistics and helps you understand the relevance of statistics to your own life. Learning checks found throughout each chapter ensure that you comprehend the material and ¬end-of-chapter problems give you the opportunity to review what you have learned. Reader-friendly examples are found throughout the book, so that you can focus on what is really going on with the numbers instead of being overwhelmed by the numbers themselves. Front Cover 1 Title Page 4 Copyright 5 Contents 10 Introduction: Methods, Material, and Moments to Remember 20 1 The What and How of Statistics 23 Before We Begin 24 A World of Information 24 Levels of Measurement 27 Samples and Populations 29 The Purposes of Statistical Analysis 32 Descriptive Statistics 32 Inferential Statistics 33 Chapter Summary 35 Some Other Things You Should Know 35 Key Terms 36 Chapter Problems 36 2 Describing Data and Distributions 38 Before We Begin 39 Measures of Central Tendency 39 The Mean 39 The Median 43 The Mode 45 Measures of Variability or Dispersion 47 The Range 47 Deviations From the Mean 48 The Mean Deviation 51 The Variance 53 The Standard Deviation 56 n Versus n – 1 63 Chapter Summary 66 Some Other Things You Should Know 66 Key Terms 67 Chapter Problems 67 3 The Shape of Distributions 71 Before We Begin 72 The Basic Elements 72 Beyond the Basics: Comparisons and Conclusions 75 A Special Curve 79 Chapter Summary 87 Some Other Things You Should Know 87 Key Terms 88 Chapter Problems 88 4 The Normal Curve 90 Before We Begin 91 Real-World Normal Curves 92 Into the Theoretical World 95 The Table of Areas Under the Normal Curve 98 Finally, an Application 104 Chapter Summary 109 Some Other Things You Should Know 109 Key Terms 110 Chapter Problems 110 5 Four Fundamental Concepts 112 Before We Begin 113 Fundamental Concept #1: Random Sampling 113 Fundamental Concept #2: Sampling Error 116 Fundamental Concept #3: The Sampling Distribution of Sample Means 118 Fundamental Concept #4: The Central Limit Theorem 119 Chapter Summary 124 Some Other Things You Should Know 124 Key Terms 125 Chapter Problems 125 6 Confidence Intervals 127 Before We Begin 128 Confidence Interval for the Mean 128 Confidence Interval for the Mean With σ Known 129 An Application 130 Reviewing Z Values 131 Z Values and the Width of the Interval 133 Bringing in the Standard Error of the Mean 133 The Relevance of the Central Limit Theorem and the Standard Error 136 Confidence and Interval Width 139 A Brief Recap 141 Confidence Interval for the Mean With σ Unknown 142 Estimating the Standard Error of the Mean 142 The Family of t Distributions 145 The Table for the Family of t Distributions 147 An Application 151 A Final Comment About the Interpretation of a Confidence Interval for the Mean 153 A Final Comment About Z Versus t 154 Confidence Intervals for Proportions 155 An Application 156 Margin of Error 158 Chapter Summary 160 Some Other Things You Should Know 162 Key Terms 163 Chapter Problems 163 7 Hypothesis Testing With a Single Sample Mean 167 Before We Begin 168 Setting the Stage 168 A Hypothesis as a Statement of Your Expectations: The Case of the Null Hypothesis 169 Single Sample Test With σ Known 171 Refining the Null and Phrasing It the Right Way 172 The Logic of the Test 173 Applying the Test 175 Levels of Significance, Critical Values, and the Critical Region 178 But What If ... 181 But What If We're Wrong? 183 Single Sample Test With σ Unknown 187 Applying the Test 188 Some Variations on a Theme 190 Chapter Summary 191 Some Other Things You Should Know 192 Key Terms 192 Chapter Problems 193 8 Hypothesis Testing With Two Samples (Mean Difference and Difference of Means) 197 Before We Begin 198 Related Samples 198 The Logic of the Test 199 The Null Hypothesis 203 Combining the Logic and the Null 203 The Estimate of the Standard Error of the Mean Difference 204 Applying the Test 204 Interpreting the Results 205 Some Additional Examples 206 Independent Samples 207 The Logic of the Test 208 The Null Hypothesis 211 Combining the Logic and the Null 211 The Estimate of the Standard Error of the Difference of Means 211 Applying the Test 214 Interpreting the Results 215 Some Additional Examples 215 Chapter Summary 217 Some Other Things You Should Know 217 Key Terms 218 Chapter Problems 218 9 Beyond the Null Hypothesis 222 Before We Begin 223 Research or Alternative Hypotheses 223 One-Tailed and Two-Tailed Test Scenarios 225 Testing a Non-directional Research Hypothesis 226 Testing a Directional Research Hypothesis 228 Power and Effect 232 Chapter Summary 236 Some Other Things You Should Know 237 Key Terms 238 Chapter Problems 238 10 Analysis of Variance 240 Before We Begin 242 The Logic of ANOVA 242 From Curves to Data Distributions 244 The Different Means 245 From Different Means to Different Types of Variation 247 The Null Hypothesis 249 The Application 250 Calculating the Within-Groups Sum of Squares (SS[sub(W)]) 251 Calculating the Between-Groups Sum of Squares (SS[sub(B)]) 254 From Sums of Squares to Estimates of Variance 256 Calculating the F Ratio 260 The Interpretation 261 Interpretation of the F Ratio 262 Post Hoc Testing 263 Chapter Summary 268 Some Other Things You Should Know 268 Key Terms 269 Chapter Problems 269 11 The Chi-Square Test 274 Before We Begin 275 The Chi-Square Test of Independence 275 The Logic of the Test 276 A Focus on the Departure From Chance 280 The Null Hypothesis 281 The Application 281 The Formula 284 The Calculation 286 Conclusion and Interpretation 287 Chapter Summary 288 Some Other Things You Should Know 289 Key Terms 290 Chapter Problems 290 12 Correlation and Regression 293 Before We Begin 294 Scatter Plots 294 Linear Associations: Direction and Strength 296 Other Types of Association 298 Correlation Analysis 299 Two Variables: X and Y 300 The Logic of Correlation 302 The Formula for Pearson's r 303 Application 306 Interpretation 308 An Additional Step: Testing the Null 310 Conclusion and Interpretation 311 Regression Analysis 312 An Application 312 The Logic of Prediction and the Line of Best Fit 314 The Regression Equation 316 The Standard Error of the Estimate 319 Chapter Summary 321 Some Other Things You Should Know 322 Key Terms 323 Chapter Problems 323 Appendix A: Table of Areas Under the Normal Curve (Distribution of Z) 328 Appendix B: Family of t Distributions (Two-Tailed Test) 330 Appendix C: Family of t Distributions (One-Tailed Test) 331 Appendix D: Distribution of F (.05 Level of Significance) 332 Appendix E: Distribution of F (.01 Level of Significance) 333 Appendix F: Distribution of Q (.05 Level of Significance) 334 Appendix G: Distribution of Q (.01 Level of Significance) 335 Appendix H: Critical Values for Chi-Square ( X[sup(2)] 336 Appendix I: Critical Values of r (Correlation Coefficient) 337 Appendix J: Data Sets and Computer-Based Data Analysis 338 It's Usually Starts With Rows and Columns 338 Good News; Words of Caution; It's Up to You 342 Appendix K: Some of the More Common Formulas Used in the Text 344 Answers to Chapter Problems 346 Glossary 352 References 358 Index 360

this Introductory Statistics Textbook Covers The Basics Of The Subject, With Chapters On The Description Of Data And Distribution, The Normal Curve, Confidence Intervals, Hypothesis Testing, Variance, The Chi-square Test, And Correlation And Regression. Caldwell Teaches Sociology At Southwest Texas State University. Annotation (c)2003 Book News, Inc., Portland, Or