Statistics: Informed Decisions Using Data (4th Edition)

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Check With The Seller Prior To Purchase. -- Michael Sullivan's Statistics: Informed Decisions Using Data, Fourth Edition, Connects Statistical Concepts To Students' Lives, Helping Them To Think Critically, Become Informed Consumers, And Make Better Decisions. Throughout The Book, Putting It Together Features Help Students Visualize The Relationships Among Various Statistical Concepts. This Feature Extends To The Exercises, Providing A Consistent Vision Of The Bigger Picture Of Statistics. This Book Follows The Guidelines For Assessment And Instruction In Statistics Education (gaise), As Recommended By The American Statistical Association, And Emphasizes Statistical Literacy, Use Of Real Data And Technology, Conceptual Understanding, And Active Learning. Cover 1 Title Page 5 Copyright Page 6 Contents 9 Preface to the Instructor 15 Supplements 21 Technology Resources 22 Applications Index 25 PART 1 Getting the Information You Need 33 CHAPTER 1 Data Collection 34 1.1 Introduction to the Practice of Statistics 35 1.2 Observational Studies versus Designed Experiments 47 1.3 Simple Random Sampling 54 1.4 Other Effective Sampling Methods 62 1.5 Bias in Sampling 70 1.6 The Design of Experiments 77 Chapter 1 Review 89 Chapter Test 93 Making an Informed Decision: What College Should I Attend? 94 Case Study: Chrysalises for Cash 95 PART 2 Descriptive Statistics 97 CHAPTER 2 Organizing and Summarizing Data 98 2.1 Organizing Qualitative Data 99 2.2 Organizing Quantitative Data: The Popular Displays 113 2.3 Additional Displays of Quantitative Data 133 2.4 Graphical Misrepresentations of Data 142 Chapter 2 Review 150 Chapter Test 154 Making an Informed Decision: Tables or Graphs? 156 Case Study: The Day the Sky Roared 157 CHAPTER 3 Numerically Summarizing Data 159 3.1 Measures of Central Tendency 160 3.2 Measures of Dispersion 173 3.3 Measures of Central Tendency and Dispersion from Grouped Data 190 3.4 Measures of Position and Outliers 196 3.5 The Five-Number Summary and Boxplots 206 Chapter 3 Review 214 Chapter Test 217 Making an Informed Decision: What Car Should I Buy? 219 Case Study: Who Was “A Mourner”? 220 CHAPTER 4 Describing the Relation between Two Variables 222 4.1 Scatter Diagrams and Correlation 223 4.2 Least-Squares Regression 239 4.3 Diagnostics on the Least-Squares Regression Line 253 4.4 Contingency Tables and Association 267 Chapter 4 Review 277 Chapter Test 282 Making an Informed Decision: Relationships among Variables on a World Scale 283 Case Study: Thomas Malthus, Population, and Subsistence 284 PART 3 Probability and Probability Distributions 285 CHAPTER 5 Probability 286 5.1 Probability Rules 287 5.2 The Addition Rule and Complements 301 5.3 Independence and the Multiplication Rule 312 5.4 Conditional Probability and the General Multiplication Rule 318 5.5 Counting Techniques 328 5.6 Putting It Together: Which Method Do I Use? 340 Chapter 5 Review 345 Chapter Test 349 Making an Informed Decision: The Effects of Drinking and Driving 350 Case Study: The Case of the Body in the Bag 351 CHAPTER 6 Discrete Probability Distributions 353 6.1 Discrete Random Variables 354 6.2 The Binomial Probability Distribution 365 6.3 The Poisson Probability Distribution 379 Chapter 6 Review 386 Chapter Test 388 Making an Informed Decision: Should We Convict? 389 Case Study: The Voyage of the St. Andrew 390 CHAPTER 7 The Normal Probability Distribution 392 7.1 Properties of the Normal Distribution 393 7.2 Applications of the Normal Distribution 402 7.3 Assessing Normality 414 7.4 The Normal Approximation to the Binomial Probability Distribution 420 Chapter 7 Review 425 Chapter Test 427 Making an Informed Decision: Stock Picking 428 Case Study: A Tale of Blood Chemistry and Health 429 PART 4 Inference: From Samples to Population 431 CHAPTER 8 Sampling Distributions 432 8.1 Distribution of the Sample Mean 433 8.2 Distribution of the Sample Proportion 445 Chapter 8 Review 453 Chapter Test 454 Making an Informed Decision: How Much Time Do You Spend in a Day . . .? 455 Case Study: Sampling Distribution of the Median 455 CHAPTER 9 Estimating the Value of a Parameter 457 9.1 Estimating a Population Proportion 458 9.2 Estimating a Population Mean 472 9.3 Estimating a Population Standard Deviation 487 9.4 Putting It Together: Which Procedure Do I Use? 493 9.5 Estimating with Bootstrapping 496 Chapter 9 Review 501 Chapter Test 504 Making an Informed Decision: How Much Should I Spend for This House? 506 Case Study: Fire-Safe Cigarettes 507 CHAPTER 10 Hypothesis Tests Regarding a Parameter 508 10.1 The Language of Hypothesis Testing 509 10.2 Hypothesis Tests for a Population Proportion 516 10.3 Hypothesis Tests for a Population Mean 529 10.4 Hypothesis Tests for a Population Standard Deviation 540 10.5 Putting It Together: Which Method Do I Use? 546 10.6 The Probability of a Type II Error and the Power of the Test 548 Chapter 10 Review 553 Chapter Test 556 Making an Informed Decision: Selecting a Mutual Fund 557 Case Study: How Old Is Stonehenge? 558 CHAPTER 11 Inferences on Two Samples 560 11.1 Inference about Two Population Proportions 561 11.2 Inference about Two Means: Dependent Samples 576 11.3 Inference about Two Means: Independent Samples 586 11.4 Inference about Two Population Standard Deviations 599 11.5 Putting It Together: Which Method Do I Use? 608 Chapter 11 Review 612 Chapter Test 616 Making an Informed Decision: Which Car Should I Buy? 617 Case Study: Control in the Design of an Experiment 618 CHAPTER 12 Inference on Categorical Data 620 12.1 Goodness-of-Fit Test 621 12.2 Tests for Independence and the Homogeneity of Proportions 631 Chapter 12 Review 646 Chapter Test 648 Making an Informed Decision: Benefits of College 649 Case Study: Feeling Lucky? Well, Are You? 650 CHAPTER 13 Comparing Three or More Means 652 13.1 Comparing Three or More Means (One-Way Analysis of Variance) 653 13.2 Post Hoc Tests on One-Way Analysis of Variance 669 13.3 The Randomized Complete Block Design 678 13.4 Two-Way Analysis of Variance 687 Chapter 13 Review 702 Chapter Test 705 Making an Informed Decision: Where Should I Invest? 707 Case Study: Hat Size and Intelligence 708 CHAPTER 14 Inference on the Least-Squares Regression Model and Multiple Regression 710 14.1 Testing the Signi.cance of the Least-Squares Regression Model 711 14.2 Confidence and Prediction Intervals 726 14.3 Multiple Regression 731 Chapter 14 Review 760 Chapter Test 763 Making an Informed Decision: Buying a Home 764 Case Study: Housing Boom 765 CHAPTER 15 Nonparametric Statistics 767 15.1 An Overview of Nonparametric Statistics 768 15.2 Runs Test for Randomness 770 15.3 Inferences about Measures of Central Tendency 777 15.4 Inferences about the Difference between Two Medians: Dependent Samples 784 15.5 Inferences about the Difference between Two Medians: Independent Samples 794 15.6 Spearman’s Rank-Correlation Test 803 15.7 Kruskal–Wallis Test 808 Chapter 15 Review 816 Chapter Test 819 Making an Informed Decision: Where Should I Live? 820 Case Study: Evaluating Alabama’s 1891 House Bill 504 821 Appendix A: Tables 823 Photo Credits 855 Answers 857 Index 943 A 943 B 943 C 943 D 945 E 946 F 947 G 947 H 947 I 948 J 948 K 948 L 948 M 949 N 950 O 950 P 951 Q 952 R 952 S 953 T 955 U 956 V 956 W 956 Y 956 Z 956 Uploaded by [StormRG] 956 Content: pt. 1. Getting the information you need -- ch. 1. Data collection -- Introduction to the practice of statistics -- Observational studies versus designed experiments -- Simple random sampling --Effective sampling methods -- Bias in sampling -- Design of experiments -- pt. 2. Descriptive statistics -- ch. 2. Organizing and summarizing data -- Organizing qualitative data -- Organizing quantitative data : the popular displays -- Additional displays of quantitative data -- Graphical misrepresentations of data -- ch. 3. Numerically summarizing data -- Measures of central tendency -- Measures of dispersion -- Measures of central tendency and dispersion from grouped data -- Measures of position and outliers -- The five-number summary and boxplots -- ch. 4. Describing the relation between two variables -- Scatter diagrams and correlation -- Least-squares regression -- Diagnostics on the least-squares regression line -- Contingency tables and association -- Nonlinear regression : transformations -- pt. 3. Probability and probability distributions -- ch. 5. Probability -- Probability rules -- The addition rule and complements -- Independence and the multiplication rule -- Conditional probability and the general multiplication rule -- Counting techniques -- Baye's rule -- ch. 6. Discrete probability distributions -- Discrete random variables -- Binomial probability distribution -- The Poisson probability distribution -- The hypergeometric probability distribution -- ch. 7. The normal probability distribution -- Properties of the normal distribution -- Applications of the normal distribution -- Assessing normality -- The normal approximation to the binomial probability distribution -- pt. 4. Inference : from samples to population -- ch. 8. Sampling distributions -- Distribution of the sample mean -- Distribution of the sample proportion -- ch. 9. Estimating the value of a parameter -- Estimating a population proportion -- Estimating a population mean -- Estimating a population standard deviation -- Estimating with bootstrapping -- ch. 10. Hypothesis tests regarding a parameter -- Language of hypothesis testing -- Hypothesis tests for a population proportion -- Hypothesis tests for a population mean -- Hypothesis tests for a population standard deviation -- Probability of a Type II error and the power of the test -- ch. 11. Inferences on two samples -- Inference about two population proportions -- Inference about two means : dependent samples -- Inference about two means : independent samples -- Inference about two population standard deviations -- ch. 12. Inference on categorical data -- Goodness-of-fit test -- Tests for independence and the homogeneity of proportions -- ch. 13. Comparing three or more means -- One-way analysis of variance -- Post hoc tests on one-way analysis of variance -- The randomized complete block design -- Two-way analysis of variance.