Statistics: Unlocking the Power of Data, 2nd Edition continues to utilize these intuitive methods like randomization and bootstrap intervals to introduce the fundamental idea of statistical inference. These methods are brought to life through authentically relevant examples, enabled through easy to use statistical software, and are accessible at very early stages of a course. The program includes the more traditional methods like t-tests, chi-square texts, etc. but only after students have developed a strong intuitive understanding of inference through randomization methods. The focus throughout is on data analysis and the primary goal is to enable students to effectively collect data, analyze data, and interpret conclusions drawn from data. The program is driven by real data and real applications. Show Preface ix Unit A: Data 1 Chapter 1. Collecting Data 2 1.1. The Structure of Data 4 1.2. Sampling from a Population 16 1.3. Experiments and Observational Studies 29 Chapter 2. Describing Data 46 2.1. Categorical Variables 48 2.2. One Quantitative Variable: Shape and Center 63 2.3. One Quantitative Variable: Measures of Spread 77 2.4. Boxplots and Quantitative/Categorical Relationships 93 2.5. Two Quantitative Variables: Scatterplot and Correlation 106 2.6. Two Quantitative Variables: Linear Regression 123 2.7. Data Visualization and Multiple Variables 137 Unit A: Essential Synthesis 161 Review Exercises 174 Projects Online Unit B: Understanding Inference 193 Chapter 3. Confidence Intervals 194 3.1. Sampling Distributions 196 3.2. Understanding and Interpreting Confidence Intervals 213 3.3. Constructing Bootstrap Confidence Intervals 228 3.4. Bootstrap Confidence Intervals using Percentiles 242 Chapter 4. Hypothesis Tests 256 4.1. Introducing Hypothesis Tests 258 4.2. Measuring Evidence with P-values 272 4.3. Determining Statistical Significance 288 4.4. A Closer Look at Testing 303 4.5. Making Connections 318 Unit B: Essential Synthesis 341 Review Exercises 351 Projects Online Unit C: Inference with Normal and t-Distributions 369 Chapter 5. Approximating with a Distribution 370 5.1. Hypothesis Tests Using Normal Distributions 372 5.2. Confidence Intervals Using Normal Distributions 387 Chapter 6. Inference for Means and Proportions 402 6.1. Inference for a Proportion 6.1-D Distribution of a Proportion 404 6.1-CI Confidence Interval for a Proportion 407 6.1-HT Hypothesis Test for a Proportion 414 6.2. Inference for a Mean 6.2-D Distribution of a Mean 419 6.2-CI Confidence Interval for a Mean 424 6.2-HT Hypothesis Test for a Mean 433 6.3. Inference for a Difference in Proportions 6.3-D Distribution of a Difference in Proportions 438 6.3-CI Confidence Interval for a Difference in Proportions 441 6.3-HT Hypothesis Test for a Difference in Proportions 446 6.4. Inference for a Difference in Means 6.4-D Distribution of a Difference in Means 452 6.4-CI Confidence Interval for a Difference in Means 455 6.4-HT Hypothesis Test for a Difference in Means 461 6.5. Paired Difference in Means 468 Unit C: Essential Synthesis 477 Review Exercises 489 Projects Online Unit D: Inference for Multiple Parameters 505 Chapter 7. Chi-Square Tests for Categorical Variables 506 7.1. Testing Goodness-of-Fit for a Single Categorical Variable 508 7.2. Testing for an Association between Two Categorical Variables 523 Chapter 8. ANOVA to Compare Means 538 8.1. Analysis of Variance 540 8.2. Pairwise Comparisons and Inference after ANOVA 563 Chapter 9. Inference for Regression 574 9.1. Inference for Slope and Correlation 576 9.2. ANOVA for Regression 591 9.3. Confidence and Prediction Intervals 603 Chapter 10. Multiple Regression 610 10.1. Multiple Predictors 612 10.2. Checking Conditions for a Regression Model 624 10.3. Using Multiple Regression 633 Unit D: Essential Synthesis 647 Review Exercises 661 Projects Online The Big Picture: Essential Synthesis 669 Exercises for the Big Picture: Essential Synthesis 683 Chapter P. Probability Basics 688 P.1. Probability Rules 690 P.2. Tree Diagrams and Bayes’ Rule 702 P.3. Random Variables and Probability Functions 709 P.4. Binomial Probabilities 716 P.5. Density Curves and the Normal Distribution 724 Appendix A. Chapter Summaries 737 Appendix B. Selected Dataset Descriptions 749 Partial Answers 761 Index General Index 783 Data Index 786
Statistics: Unlocking the Power of Data, 2nd Edition Loose-leaf Print Companioncontinues to utilize these intuitive methods like randomization and bootstrap intervals to introduce the fundamental idea of statistical inference. These methods are brought to life through authentically relevant examples, enabled through easy to use statistical software, and are accessible at very early stages of a course. The program includes the more traditional methods like t-tests, chi-square texts, etc. but only after students have developed a strong intuitive understanding of inference through randomization methods. The focus throughout is on data analysis and the primary goal is to enable students to effectively collect data, analyze data, and interpret conclusions drawn from data. The program is driven by real data and real applications. "synopsis" may belong to another edition of this title. From the Back Cover: Included with this package:
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Seller Image Statistics: Unlocking the Power of Data, Second Edition Loose-leaf Print Companion Loose LeafLock, Robin H.", "Lock, Patti Frazer", "Lock Morgan, Kari", "Lock, Eric F.", "Lock, Dennis F." Published by Wiley (2016) ISBN 10: 1119163668 ISBN 13: 9781119163664 New No Binding Quantity: 20 Book Description No Binding. Condition: new. Seller Inventory # 9781119163664 More information about this seller | Contact this seller |