Introductory Statistics, Third Edition

In this 3rd edition revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. Concepts are motivated, illustrated and explained in a way that attempts to increase one's intuition. To quote from the preface, "It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data." Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples. Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud and many others. Ancillary list: Instructor's Manual - http://textbooks.elsevier.com/web/manuals.aspx?isbn=9780123743886 Student Solutions Manual - http://www.elsevierdirect.com/product.jsp?isbn=9780123743886 Student Solutions Manual for 2nd Edition - http://www.elsevierdirect.com/product.jsp?isbn=9780120885510 Sample Chapter, eBook - http://www.elsevierdirect.com/product.jsp?isbn=9780123743886 Companion Website w/Data Sets - http://www.elsevierdirect.com/companion.jsp?ISBN=9780123743886 Unique historical perspective profiling prominent statisticians and historical events to motivate learning by providing interest and context Use of exercises and examples helps guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, scientific fraud. Summary/Key Terms- chapters end with detailed reviews of important concepts and formulas, key terms and definitions which are useful to students as study tools Data sets from text and exercise material will be available to download from the text website, saves students time Cover......Page 1 Introductory Statistics......Page 4 About the Author......Page 6 Contents......Page 8 Preface......Page 18 Acknowledgments......Page 22 1.1 Introduction......Page 24 1.2 The Nature of Statistics......Page 26 1.3 Populations and Samples......Page 28 1.4 A Brief History of Statistics......Page 30 Key Terms......Page 33 Review Problems......Page 34 CHAPTER 2 Describing Data Sets......Page 40 2.2 Frequency Tables and Graphs......Page 41 2.3 Grouped Data and Histograms......Page 55 2.4 Stem-and-Leaf Plots......Page 67 2.5 Sets of Paired Data......Page 74 2.6 Some Historical Comments......Page 81 Key Terms......Page 82 Summary......Page 83 Review Problems......Page 86 CHAPTER 3 Using Statistics to Summarize Data Sets......Page 94 3.1 Introduction......Page 95 3.2 Sample Mean......Page 96 3.3 Sample Median......Page 106 3.4 Sample Mode......Page 120 3.5 Sample Variance and Sample Standard Deviation......Page 122 3.6 Normal Data Sets and the Empirical Rule......Page 132 3.7 Sample Correlation Coefficient......Page 143 Key Terms......Page 157 Summary......Page 159 Review Problems......Page 161 CHAPTER 4 Probability......Page 168 4.2 Sample Space and Events of an Experiment......Page 169 4.3 Properties of Probability......Page 176 4.4 Experiments Having Equally Likely Outcomes......Page 184 4.5 Conditional Probability and Independence......Page 190 4.6 Bayes’ Theorem......Page 208 4.7 Counting Principles......Page 212 Key Terms......Page 221 Summary......Page 223 Review Problems......Page 224 CHAPTER 5 Discrete Random Variables......Page 232 5.1 Introduction......Page 233 5.2 Random Variables......Page 234 5.3 Expected Value......Page 241 5.4 Variance of Random Variables......Page 254 5.5 Binomial Random Variables......Page 261 5.6 Hypergeometric Random Variables......Page 271 5.7 Poisson Random Variables......Page 273 Summary......Page 277 Review Problems......Page 279 CHAPTER 6 Normal Random Variables......Page 284 6.2 Continuous Random Variables......Page 285 6.3 Normal Random Variables......Page 289 6.4 Probabilities Associated with a Standard Normal Random Variable......Page 294 6.5 Finding Normal Probabilities: Conversion to the Standard Normal......Page 300 6.6 Additive Property of Normal Random Variables......Page 302 6.7 Percentiles of Normal Random Variables......Page 307 Summary......Page 313 Review Problems......Page 316 CHAPTER 7 Distributions of Sampling Statistics......Page 320 7.2 Introduction......Page 321 7.3 Sample Mean......Page 322 7.4 Central Limit Theorem......Page 327 7.5 Sampling Proportions from a Finite Population......Page 336 7.6 Distribution of the Sample Variance of a Normal Population......Page 346 Key Terms......Page 348 Summary......Page 349 Review Problems......Page 350 CHAPTER 8 Estimation......Page 354 8.1 Introduction......Page 355 8.2 Point Estimator of a Population Mean......Page 356 8.3 Point Estimator of a Population Proportion......Page 359 8.4 Estimating a Population Variance......Page 365 8.5 Interval Estimators of the Mean of a Normal Population with Known Population Variance......Page 370 8.6 Interval Estimators of the Mean of a Normal Population with Unknown Population Variance......Page 382 8.7 Interval Estimators of a Population Proportion......Page 394 Key Terms......Page 403 Summary......Page 404 Review Problems......Page 406 CHAPTER 9 Testing Statistical Hypotheses......Page 410 9.2 Hypothesis Tests and Significance Levels......Page 411 9.3 Tests Concerning the Mean of a Normal Population: Case of Known Variance......Page 417 9.4 The t Test for the Mean of a Normal Population: Case of Unknown Variance......Page 432 9.5 Hypothesis Tests Concerning Population Proportions......Page 444 Summary......Page 456 Review Problems and Proposed Case Studies......Page 460 CHAPTER 10 Hypothesis Tests Concerning Two Populations......Page 466 10.1 Introduction......Page 467 10.2 Testing Equality of Means of Two Normal Populations: Case of Known Variances......Page 469 10.3 Testing Equality of Means: Unknown Variances and Large Sample Size......Page 476 10.4 Testing Equality of Means: Small-Sample Tests when the Unknown Population Variances Are Equal......Page 486 10.5 Paired-Sample t Test......Page 494 10.6 Testing Equality of Population Proportions......Page 504 Summary......Page 516 Review Problems......Page 521 CHAPTER 11 Analysis of Variance......Page 526 11.1 Introduction......Page 527 11.2 One-Factor Analysis of Variance......Page 528 11.3 Two-Factor Analysis of Variance: Introduction and Parameter Estimation......Page 537 11.4 Two-Factor Analysis of Variance: Testing Hypotheses......Page 543 11.5 Final Comments......Page 552 Summary......Page 553 Review Problems......Page 556 CHAPTER 12 Linear Regression......Page 560 12.1 Introduction......Page 562 12.2 Simple Linear Regression Model......Page 563 12.3 Estimating the Regression Parameters......Page 567 12.4 Error Random Variable......Page 576 12.5 Testing the Hypothesis that β =0......Page 580 12.6 Regression to the Mean......Page 587 12.7 Prediction Intervals for Future Responses......Page 596 12.8 Coefficient of Determination......Page 601 12.9 Sample Correlation Coefficient......Page 605 12.10 Analysis of Residuals: Assessing the Model......Page 607 12.11 Multiple Linear Regression Model......Page 609 Summary......Page 618 Review Problems......Page 622 CHAPTER 13 Chi-Squared Goodness-of-Fit Tests......Page 628 13.1 Introduction......Page 629 13.2 Chi-Squared Goodness-of-Fit Tests......Page 632 13.3 Testing for Independence in Populations Classified According to Two Characteristics......Page 643 13.4 Testing for Independence in Contingency Tables with Fixed Marginal Totals......Page 654 Key Terms......Page 660 Summary......Page 661 Review Problems......Page 663 CHAPTER 14 Nonparametric Hypotheses Tests......Page 670 14.2 Sign Test......Page 671 14.3 Signed-Rank Test......Page 680 14.4 Rank-Sum Test for Comparing Two Populations......Page 690 14.5 Runs Test for Randomness......Page 699 14.6 Testing the Equality of Multiple Probability Distributions......Page 706 14.7 Permutation Tests......Page 712 Summary......Page 716 Review Problems......Page 719 CHAPTER 15 Quality Control......Page 722 15.2 The X Control Chart for Detecting a Shift in the Mean......Page 723 15.3 Control Charts for Fraction Defective......Page 738 15.4 Exponentially Weighted Moving-Average Control Charts......Page 740 15.5 Cumulative-Sum Control Charts......Page 745 Summary......Page 748 Review Problems......Page 749 APPENDICES......Page 750 A - A Data Set......Page 752 B - Mathematical Preliminaries......Page 756 C - How to Choose a Random Sample......Page 758 D - Tables......Page 762 E - Programs......Page 778 Answers to Odd-Numbered Problems......Page 780 Index......Page 830 Academic Press Cover 1 Introductory Statistics 4 About the Author 6 Contents 8 Preface 18 Acknowledgments 22 CHAPTER 1 Introduction to Statistics 24 1.1 Introduction 24 1.2 The Nature of Statistics 26 1.3 Populations and Samples 28 1.4 A Brief History of Statistics 30 Key Terms 33 The Changing Definition of Statistics 34 Review Problems 34 CHAPTER 2 Describing Data Sets 40 2.1 Introduction 41 2.2 Frequency Tables and Graphs 41 2.3 Grouped Data and Histograms 55 2.4 Stem-and-Leaf Plots 67 2.5 Sets of Paired Data 74 2.6 Some Historical Comments 81 Key Terms 82 Summary 83 Review Problems 86 CHAPTER 3 Using Statistics to Summarize Data Sets 94 3.1 Introduction 95 3.2 Sample Mean 96 3.3 Sample Median 106 3.4 Sample Mode 120 3.5 Sample Variance and Sample Standard Deviation 122 3.6 Normal Data Sets and the Empirical Rule 132 3.7 Sample Correlation Coefficient 143 Key Terms 157 Summary 159 Review Problems 161 CHAPTER 4 Probability 168 4.1 Introduction 169 4.2 Sample Space and Events of an Experiment 169 4.3 Properties of Probability 176 4.4 Experiments Having Equally Likely Outcomes 184 4.5 Conditional Probability and Independence 190 4.6 Bayes’ Theorem 208 4.7 Counting Principles 212 Key Terms 221 Summary 223 Review Problems 224 CHAPTER 5 Discrete Random Variables 232 5.1 Introduction 233 5.2 Random Variables 234 5.3 Expected Value 241 5.4 Variance of Random Variables 254 5.5 Binomial Random Variables 261 5.6 Hypergeometric Random Variables 271 5.7 Poisson Random Variables 273 Key Terms 277 Summary 277 Review Problems 279 CHAPTER 6 Normal Random Variables 284 6.1 Introduction 285 6.2 Continuous Random Variables 285 6.3 Normal Random Variables 289 6.4 Probabilities Associated with a Standard Normal Random Variable 294 6.5 Finding Normal Probabilities: Conversion to the Standard Normal 300 6.6 Additive Property of Normal Random Variables 302 6.7 Percentiles of Normal Random Variables 307 Key Terms 313 Summary 313 Review Problems 316 CHAPTER 7 Distributions of Sampling Statistics 320 7.1 A Preview 321 7.2 Introduction 321 7.3 Sample Mean 322 7.4 Central Limit Theorem 327 7.5 Sampling Proportions from a Finite Population 336 7.6 Distribution of the Sample Variance of a Normal Population 346 Key Terms 348 Summary 349 Review Problems 350 CHAPTER 8 Estimation 354 8.1 Introduction 355 8.2 Point Estimator of a Population Mean 356 8.3 Point Estimator of a Population Proportion 359 8.4 Estimating a Population Variance 365 8.5 Interval Estimators of the Mean of a Normal Population with Known Population Variance 370 8.6 Interval Estimators of the Mean of a Normal Population with Unknown Population Variance 382 8.7 Interval Estimators of a Population Proportion 394 Key Terms 403 Summary 404 Review Problems 406 CHAPTER 9 Testing Statistical Hypotheses 410 9.1 Introduction 411 9.2 Hypothesis Tests and Significance Levels 411 9.3 Tests Concerning the Mean of a Normal Population: Case of Known Variance 417 9.4 The t Test for the Mean of a Normal Population: Case of Unknown Variance 432 9.5 Hypothesis Tests Concerning Population Proportions 444 Key Terms 456 Summary 456 Review Problems and Proposed Case Studies 460 CHAPTER 10 Hypothesis Tests Concerning Two Populations 466 10.1 Introduction 467 10.2 Testing Equality of Means of Two Normal Populations: Case of Known Variances 469 10.3 Testing Equality of Means: Unknown Variances and Large Sample Size 476 10.4 Testing Equality of Means: Small-Sample Tests when the Unknown Population Variances Are Equal 486 10.5 Paired-Sample t Test 494 10.6 Testing Equality of Population Proportions 504 Key Terms 516 Summary 516 Review Problems 521 CHAPTER 11 Analysis of Variance 526 11.1 Introduction 527 11.2 One-Factor Analysis of Variance 528 11.3 Two-Factor Analysis of Variance: Introduction and Parameter Estimation 537 11.4 Two-Factor Analysis of Variance: Testing Hypotheses 543 11.5 Final Comments 552 Key Terms 553 Summary 553 Review Problems 556 CHAPTER 12 Linear Regression 560 12.1 Introduction 562 12.2 Simple Linear Regression Model 563 12.3 Estimating the Regression Parameters 567 12.4 Error Random Variable 576 12.5 Testing the Hypothesis that β =0 580 12.6 Regression to the Mean 587 12.7 Prediction Intervals for Future Responses 596 12.8 Coefficient of Determination 601 12.9 Sample Correlation Coefficient 605 12.10 Analysis of Residuals: Assessing the Model 607 12.11 Multiple Linear Regression Model 609 Key Terms 618 Summary 618 Review Problems 622 CHAPTER 13 Chi-Squared Goodness-of-Fit Tests 628 13.1 Introduction 629 13.2 Chi-Squared Goodness-of-Fit Tests 632 13.3 Testing for Independence in Populations Classified According to Two Characteristics 643 13.4 Testing for Independence in Contingency Tables with Fixed Marginal Totals 654 Key Terms 660 Summary 661 Review Problems 663 CHAPTER 14 Nonparametric Hypotheses Tests 670 14.1 Introduction 671 14.2 Sign Test 671 14.3 Signed-Rank Test 680 14.4 Rank-Sum Test for Comparing Two Populations 690 14.5 Runs Test for Randomness 699 14.6 Testing the Equality of Multiple Probability Distributions 706 14.7 Permutation Tests 712 Key Terms 716 Summary 716 Review Problems 719 CHAPTER 15 Quality Control 722 15.1 Introduction 723 15.2 The X Control Chart for Detecting a Shift in the Mean 723 15.3 Control Charts for Fraction Defective 738 15.4 Exponentially Weighted Moving-Average Control Charts 740 15.5 Cumulative-Sum Control Charts 745 Key Terms 748 Summary 748 Review Problems 749 APPENDICES 750 A - A Data Set 752 B - Mathematical Preliminaries 756 C - How to Choose a Random Sample 758 D - Tables 762 E - Programs 778 Answers to Odd-Numbered Problems 780 Index 830 9780123743886

In this 3rd edition revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. Concepts are motivated, illustrated and explained in a way that attempts to increase one's intuition. To quote from the preface, "It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data."

Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples.

Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud and many others.

Ancillary list:

• Instructor's Manual - http://textbooks.elsevier.com/web/manuals.aspx?isbn=9780123743886
• Student Solutions Manual - http://www.elsevierdirect.com/product.jsp?isbn=9780123743886
• Student Solutions Manual for 2nd Edition - http://www.elsevierdirect.com/product.jsp?isbn=9780120885510
• Sample Chapter, eBook - http://www.elsevierdirect.com/product.jsp?isbn=9780123743886
• Companion Website w/Data Sets - http://www.elsevierdirect.com/companion.jsp?ISBN=9780123743886

• Unique historical perspective profiling prominent statisticians and historical events to motivate learning by providing interest and context
• Use of exercises and examples helps guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, scientific fraud.
• Summary/Key Terms- chapters end with detailed reviews of important concepts and formulas, key terms and definitions which are useful to students as study tools
• Data sets from text and exercise material will be available to download from the text website, saves students time
  
  
  
  
  
  
  
  
  
  
  
  
  
  

Introductory Statistics, Third Edition, presents statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also to understand why these procedures should be used. This book offers a unique historical perspective, profiling prominent statisticians and historical events in order to motivate learning. To help guide students towards independent learning, exercises and examples using real issues and real data (e.g., stock price models, health issues, gender issues, sports, scientific fraud) are provided. The chapters end with detailed reviews of important concepts and formulas, key terms, and definitions that are useful study tools. Data sets from text and exercise material are available for download in the text website. This text is designed for introductory non-calculus based statistics courses that are offered by mathematics and/or statistics departments to undergraduate students taking a semester course in basic Statistics or a year course in Probability and Statistics. Unique historical perspective profiling prominent statisticians and historical events to motivate learning by providing interest and context Use of exercises and examples helps guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, scientific fraud. Summary/Key Terms- chapters end with detailed reviews of important concepts and formulas, key terms and definitions which are useful to students as study tools This handy supplement shows students how to come to the answers shown in the back of the text. It includes solutions to all of the odd numbered exercises. The text itself: In this second edition, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, examples and applications from diverse areas, and most importantly, an explanation of intuition and ideas behind the statistical methods. To quote from the preface, "it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data." Consistent with his other excellent books in Probability and Stochastic Modeling, Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples. "In this revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas. Ross provides a clear explanation of intuition and the ideas behind the statistical methods. To quote from the preface, "It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data." Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples."--Publisher's website A work in introductory statistics, which provides an explanation of intuition and ideas behind the statistical methods. It includes a supplement which shows students how to come to the answers shown in the back of the text. It includes solutions to all of the odd numbered exercises.