Robert S. Witte (San Jose State University), John S. Witte (Case Western Reserve University)

Statistics

• Broschiertes Buch

Produktbeschreibung

Drawing upon over 40 years of experience, the authors of Statistics, 11th Edition provide students with a clear and methodical approach to essential statistical procedures. The text clearly explains the basic concepts and procedures of descriptive and inferential statistical analysis. It features an emphasis on expressions involving sums of squares and degrees of freedom as well as a strong stress on the importance of variability. This accessible approach will help students tackle such perennially mystifying topics as the standard deviation, variance interpretation of the correlation coefficient, hypothesis tests, degrees of freedom, p-values, and estimates of effect size.

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Produktdetails

• Verlag: John Wiley & Sons Inc
• 11 ed
• Seitenzahl: 496
• Erscheinungstermin: 16. März 2021
• Englisch
• Abmessung: 251mm x 211mm x 25mm
• Gewicht: 1058g
• ISBN-13: 9781119254515
• ISBN-10: 1119254515
• Artikelnr.: 66532524

Autorenporträt

Robert Witte earned his Ph.D. at Stanford University. He is an Emeritus Professor of Psychology at San Jose State University, where he taught courses in statistics for more than three decades. He has had a number of publications in peer-reviewed journals, as well as a number of nationally-competitive research grants and a post-doctoral Research Fellowship at Indiana University.   John Witte is Professor of Epidemiology and Biostatistics at the University of California, San Francisco.  He received his PhD from the University of California, Los Angeles, and was previously on the faculty at the University of Southern California and Case Western Reserve University. He has published over 150 papers, and his research is primarily focused on statistical genetics and the genetic epidemiology of cancer. 

Inhaltsangabe

Preface iv Acknowledgments vi 1 Introduction 3 1.1 Why Study Statistics? 4 1.2 What Is Statistics? 4 1.3 More about Inferential Statistics 6 1.4 Three Types of Data 9 1.5 Levels of Measurement 10 1.6 Types of Variables 14 1.7 How to Use This Book 19 Summary 20 Important Terms 21 Review Questions 21 PART 1 Descriptive Statistics: Organizing and Summarizing Data 25 2 Describing Data with Tables and Graphs 27 Tables (Frequency Distributions) 28 2.1 Frequency Distributions for Quantitative Data 28 2.2 Guidelines 29 2.3 Outliers 34 2.4 Relative Frequency Distributions 35 2.5 Cumulative Frequency Distributions 36 2.6 Frequency Distributions for Qualitative (Nominal) Data 38 2.7 Interpreting Distributions Constructed By Others 39 Graphs 40 2.8 Graphs for Quantitative Data 40 2.9 Typical Shapes 45 2.10 A Graph for Qualitative (Nominal) Data 47 2.11 Misleading Graphs 48 2.12 Doing It Yourself 50 Summary 50 Important Terms 52 Review Questions 53 3 Describing Data with Averages 59 3.1 Mode 60 3.2 Median 61 3.3 Mean 63 3.4 Which Average? 65 3.5 Averages for Qualitative and Ranked Data 68 Summary 70 Important Terms 70 Key Equation 71 Review Questions 71 4 Describing Variability 75 4.1 Intuitive Approach 76 4.2 Range 78 4.3 Variance 78 4.4 Standard Deviation 79 4.5 Details: Standard Deviation 84 4.6 Degrees Of Freedom (df ) 92 4.7 Interquartile Range (IQR) 94 4.8 Measures of Variability for Qualitative and Ranked Data 95 Summary 95 Important Terms 96 Key Equations 97 Review Questions 97 5 Normal Distributions and Standard (z) Scores 101 5.1 The Normal Curve 103 5.2 z Scores 105 5.3 Standard Normal Curve 106 5.4 Solving Normal Curve Problems 109 5.5 Finding Proportions 110 5.6 Finding Scores 116 5.7 More About z Scores 121 Summary 124 Important Terms 125 Key Equations 125 Review Questions 125 6 Describing Relationships: Correlation 131 6.1 An Intuitive Approach 132 6.2 Scatterplots 134 6.3 A Correlation Coefficient for Quantitative Data: R 137 6.4 Details: Computation Formula for r 142 6.5 Outliers Again 144 6.6 Other Types of Correlation Coefficients 145 6.7 Computer Output 146 Summary 149 Important Terms and Symbols 150 Key Equations 150 Review Questions 151 7 Regression 155 7.1 Two Rough Predictions 156 7.2 A Regression Line 157 7.3 Least Squares Regression Line 159 7.4 Standard Error of Estimate, sy x 163 7.5 Assumptions 166 7.6 Interpretation of R2 167 7.7 Multiple Regression Equations 172 7.8 Regression Toward The Mean 172 Summary 175 Important Terms 175 Key Equations 175 Review Exercises 176 PART 2 Inferential Statistics: Generalizing Beyond Data 179 8 Populations, Samples, and Probability 181 Populations and Samples 182 8.1 Populations 182 8.2 Samples 183 8.3 Random Sampling 184 8.4 Tables of Random Numbers 185 8.5 Random Assignment of Subjects 186 8.6 Surveys or Experiments? 188 Probability 188 8.7 Definition 189 8.8 Addition Rule 189 8.9 Multiplication Rule 191 8.10 Probability and Statistics 195 Summary 197 Important Terms 197 Key Equations 198 Review Questions 198 9 Sampling Distribution of the Mean 205 9.1 What Is A Sampling Distribution? 206 9.2 Creating a Sampling Distribution from Scratch 207 9.3 Some Important Symbols 209 9.4 Mean of All Sample Means (uX ) 211 9.5 Standard Error of The Mean (
X ) 212 9.6 Shape of the Sampling Distribution 214 9.7 Other Sampling Distributions 216 Summary 217 Important Terms 217 Key Equations 217 Review Questions 218 10 Introduction to Hypothesis Testing: The z Test 221 10.1 Testing a Hypothesis about Sat Scores 222 10.2 z Test for a Population Mean 224 10.3 Step-By-Step Procedure 226 10.4 Statement of the Research Problem 226 10.5 Null Hypothesis H0 227 10.6 Alternative Hypothesis H1 228 10.7 Decision Rule 229 10.8 Calculations 230 10.9 Decision 230 10.10 Interpretation 231 Summary 232 Important Terms 233 Key Equations 233 Review Questions 234 11 MORE ABOUT HYPOTHESIS TESTING 237 11.1 Why Hypothesis Tests? 238 11.2 Strong or Weak Decisions 240 11.3 One-Tailed and Two-Tailed Tests 241 11.4 Choosing a Level of Significance 
245 11.5 Testing a Hypothesis about Vitamin C 247 11.6 Four Possible Outcomes 247 11.7 If H0 Really Is True 250 11.8 If H0 Really Is False Because of a Large Effect 251 11.9 If H0 Really Is False Because of a Small Effect 254 11.10 Influence of Sample Size 255 11.11 Power and Sample Size 258 Summary 261 Important Terms 263 Review Questions 263 12 Estimation (Confidence Intervals) 267 12.1 Point Estimate for 
268 12.2 Confidence Interval (CI) FOR µ 268 12.3 Interpretation of a Confidence Interval 272 12.4 Level of Confidence 273 12.5 Effect of Sample Size 274 12.6 Hypothesis Tests or Confidence Intervals? 274 12.7 Confidence Interval for Population Percent 275 Summary 277 Important Terms 278 Key Equation 278 Review Questions 278 13 t Test for One Sample 281 13.1 Gas Mileage Investigation 282 13.2 Sampling Distribution of t 282 13.3 t Test 286 13.4 Common Theme of Hypothesis Tests 286 13.5 Reminder about Degrees of Freedom 287 13.6 Details: Estimating The Standard Error (sX-) 287 13.7 Details: Calculations for the t Test 288 13.8 Confidence Intervals for m Based on t 290 13.9 Assumptions 291 Summary 291 Important Terms 292 Key Equations 292 Review Questions 292 14 t Test for Two Independent Samples 295 14.1 EPO Experiment 296 14.2 Statistical Hypotheses 297 14.3 Sampling Distribution X-overbar1 - X-overbar2 299 14.4 t Test 301 14.5 Details: Calculations for the t Test 302 14.6 p-Values 306 14.7 Statistically Significant Results 309 14.8 Estimating Effect Size: Point Estimates and Confidence Intervals 311 14.9 Estimating Effect Size: Cohen's d 314 14.10 Meta-Analysis 316 14.11 Reports in the Literature 317 14.12 Assumptions 319 14.13 Computer Output 319 Summary 320 Important Terms 321 Key Equations 321 Review Questions 322 15 t Test for Two Related Samples (Repeated Measures) 327 15.1 EPO Experiment with Repeated Measures 328 15.2 Statistical Hypotheses 331 15.3 Sampling Distribution of D-overbar 332 15.4 t Test 332 15.5 Details: Calculations for the t Test 333 15.6 Estimating Effect Size 336 15.7 Assumptions 338 15.8 Overview: Three t Tests for Population Means 338 15.9 t Test for The Population Correlation Coefficient, r 341 Summary 343 Important Terms 344 Key Equations 344 Review Questions 345 16 Analysis of Variance (One Factor) 349 16.1 Testing a Hypothesis about Sleep Deprivation and Aggression 350 16.2 Two Sources of Variability 352 16.3 F Test 354 16.4 Details: Variance Estimates 356 16.5 Details: Mean Squares (MS) and the F Ratio 362 16.6 Table for the F Distribution 364 16.7 ANOVA Summary Tables 365 16.8 F Test Is Nondirectional 367 16.9 Estimating Effect Size 367 16.10 Multiple Comparisons 370 16.11 Overview: Flow Chart for ANOVA 374 16.12 Reports in the Literature 374 16.13 Assumptions 376 16.14 Computer Output 376 Summary 376 Important Terms 378 Key Equations 378 Review Questions 378 17 Analysis of Variance (Repeated Measures) 383 17.1 Sleep Deprivation Experiment with Repeated Measures 384 17.2 F Test 385 17.3 Two Complications 387 17.4 Details: Variance Estimates 387 17.5 Details: Mean Square (MS) and the F Ratio 391 17.6 Table for F Distribution 393 17.7 ANOVA Summary Tables 393 17.8 Estimating Effect Size 395 17.9 Multiple Comparisons 396 17.10 Reports in the Literature 398 17.11 Assumptions 399 Summary 399 Important Terms 400 Key Equations 400 Review Questions 400 18 Analysis of Variance (Two Factors) 405 18.1 A Two-Factor Experiment: Responsibility in Crowds 406 18.2 Three F Tests 409 18.3 Interaction 410 18.4 Details: Variance Estimates 414 18.5 Details: Mean Squares (MS) and F Ratios 418 18.6 Table for the F Distribution 420 18.7 Estimating Effect Size 420 18.8 Multiple Comparisons 421 18.9 Simple Effects 422 18.10 Overview: Flow Chart for Two-Factor ANOVA 426 18.11 Reports in the Literature 427 18.12 Assumptions 428 18.13 Other Types of ANOVA 428 Summary 429 Important Terms 429 Key Equations 429 Review Questions 430 19 Chi-Square (X2) Test For Qualitative (Nominal) Data 435 One-Variable X2 Test 436 19.1 Survey of Blood Types 436 19.2 Statistical Hypotheses 436 19.3 Details: Calculating X2 437 19.4 Table for the X2 Distribution 440 19.5 X2 Test 440 Two-Variable X2 Test 443 19.6 Lost Letter Study 443 19.7 Statistical Hypotheses 444 19.8 Details: Calculating X2 445 19.9 Table for The X2 Distribution 446 19.10 X2 Test 448 19.11 Estimating Effect Size 449 19.12 Odds Ratios 450 19.13 Reports in the Literature 452 19.14 Some Precautions 453 19.15 Computer Output 454 Summary 455 Important Terms 455 Key Equations 455 Review Questions 456 20 Tests for Ranked (Ordinal) Data 461 20.1 Use Only When Appropriate 462 20.2 A Note on Terminology 462 20.3 Mann-Whitney U Test (Two Independent Samples) 463 20.4 Wilcoxon T Test (Two Related Samples) 468 20.5 Kruskal-Wallis H Test (Three or More Independent Samples) 472 20.6 General Comment: Ties 476 Summary 476 Important Terms 477 Review Questions 477 21 Postscript: Which Test? 481 21.1 Descriptive or Inferential Statistics? 482 21.2 Hypothesis Tests or Confidence Intervals? 482 21.3 Quantitative or Qualitative Data? 483 21.4 Distinguishing Between the Two Types of Data 484 21.5 One, Two, or More Groups? 485 21.6 Concluding Comments 486 Review Questions 486 Appendices 489 A Math Review 489 B Answers to Selected Questions 497 C Tables 535 D Glossary 549 Photo Credits 555 Index 556