Statistics: Learning from Data (with JMP and JMP Statistical Discovery Software Printed Access Card)

Collecting data in reasonable ways -- Graphical methods for describing data distributions -- Numerical methods for describing data distributions -- Describing bivariate numerical data -- Probability -- Random variables and probability distributions -- An overview of statistical inference, learning from data -- Sampling variability and sampling distributions -- Estimating a population proportion -- Asking and answering questions about a population proportion -- Asking and answering questions about the difference between two population proportions -- Asking and answering questions about a population mean -- Asking and answering questions about the difference between two population means -- Learning from experimental data -- Learning from categorical data -- Understanding relationships, numerical data part 2 -- Asking and answering questions about more than two means. Cover 1 Title 2 Statement 3 Copyright 4 Dedication 5 Author Bio 6 Brief Contents 7 Contents 8 Preface 14 Overview 24 Ch 1: Collecting Data in Reasonable Ways 30 Preview 30 Chapter Learning Objectives 31 Section 1.1: Statistical Studies: Observation and Experimentation 31 Section 1.2: Collecting Data: Planning an Observational Study 35 Section 1.3: Collecting Data–Planning an Experiment 44 Section 1.4: The Importance of Random Selection and Random Assignment: What Types of Conclusions Are Reasonable? 53 Section 1.5: Avoid These Common Mistakes 57 Chapter Activities 58 Exploring the Big Ideas 59 Are You Ready to Move On? Chapter 1: Review Exercises 60 Ch 2: Graphical Methods for Describing Data Distributions 66 Preview 66 Chapter Learning Objectives 67 Preview Example: Love Those New Cars? 67 Section 2.1: Selecting an Appropriate Graphical Display 68 Section 2.2: Displaying Categorical Data: Bar Charts and Comparative Bar Charts 72 Section 2.3: Displaying Numerical Data: Dotplots, Stem-and-Leaf Displays, and Histograms 78 Section 2.4: Displaying Bivariate Numerical Data: Scatterplots and Time Series Plots 103 Section 2.5: Graphical Displays in the Media 108 Section 2.6: Avoid These Common Mistakes 114 Chapter Activities 117 Exploring the Big Ideas 118 Are You Ready to Move On? Chapter 2: Review Exercises 120 Technology Notes 124 Ch 3: Numerical Methods for Describing Data Distributions 132 Preview 132 Chapter Learning Objectives 133 Preview Example: Brain Blood Volume and Marijuana Use 133 Section 3.1: Selecting Appropriate Numerical Summaries 134 Section 3.2: Describing Center and Spread for Data Distributions That Are Approximately Symmetric 137 Section 3.3: Describing Center and Spread for Data Distributions That Are Skewed or Have Outliers 146 Section 3.4: Summarizing a Data Set: Boxplots 153 Section 3.5: Measures of Relative Standing: z-scores and Percentiles 164 Section 3.6: Avoid These Common Mistakes 168 Chapter Activities 169 Exploring the Big Ideas 170 Are You Ready to Move On? Chapter 3: Review Exercises 172 Technology Notes 174 Ch 4: Describing Bivariate Numerical Data 180 Preview 180 Chapter Learning Objectives 181 Preview Example: Help for Crime Scene Investigators 182 Section 4.1: Correlation 182 Section 4.2: Linear Regression: Fitting a Line to Bivariate Data 198 Section 4.3: Assessing the Fit of a Line 211 Section 4.4: Describing Linear Relationships and Making Predictions—Putting It All Together 229 Section 4.5: Avoid These Common Mistakes 231 Chapter Activities 232 Exploring the Big Ideas 233 Are You Ready to Move On? Chapter 4: Review Exercises 234 Technology Notes 238 Ch 5: Probability 242 Preview 242 Chapter Learning Objectives 243 Preview Example: Should You Paint the Nursery Pink? 243 Section 5.1: Interpreting Probabilities 244 Section 5.2: Calculating Probabilities 249 Section 5.3: Probabilities of More Complex Events: Unions, Intersections, and Complements 254 Section 5.4: Conditional Probability 266 Section 5.5: Probability as a Basis for Making Decisions 278 Section 5.6: Estimating Probabilities Empirically and Using Simulation (Optional) 281 Chapter Activities 290 Are You Ready to Move On? Chapter 5: Review Exercises 291 Ch 6: Random Variables and Probability Distributions 296 Preview 296 Chapter Learning Objectives 297 Preview Example: iPod Shuffles 297 Section 6.1: Random Variables 298 Section 6.2: Probability Distributions for Discrete Random Variables 301 Section 6.3: Probability Distributions for Continuous Random Variables 307 Section 6.4: Mean and Standard Deviation of a Random Variable 314 Section 6.5: Normal Distributions 320 Section 6.6: Checking for Normality 337 Section 6.7: Binomial and Geometric Distributions (Optional) 341 Section 6.8: Using the Normal Distribution to Approximate a Discrete Distribution (Optional) 351 Chapter Activities 356 Are You Ready to Move On? Chapter 6: Review Exercises 356 Technology Notes 359 Ch 7: An Overview of Statistical Inference—Learning from Data 364 Preview 364 Chapter Learning Objectives 365 Preview Example: Deception in Online Dating Profiles 365 Section 7.1: Statistical Inference—What You Can Learn from Data 366 Section 7.2: Selecting an Appropriate Method—Four Key Questions 372 Section 7.3: A Five-Step Process for Statistical Inference 378 Chapter Activities 379 Are You Ready to Move On? Chapter 7: Review Exercises 380 Ch 8: Sampling Variability and Sampling Distributions 382 Preview 382 Chapter Learning Objectives 383 Preview Example 383 Section 8.1: Statistics and Sampling Variability 385 Section 8.2: The Sampling Distribution of a Sample Proportion 390 Section 8.3: How Sampling Distributions Support Learning from Data 395 Chapter Activities 400 Exploring the Big Ideas 400 Are You Ready to Move On? Chapter 8: Review Exercises 401 Ch 9: Estimating a Population Proportion 404 Preview 404 Chapter Learning Objectives 405 Preview Example: Hurricane Evacuation 405 Section 9.1: Selecting an Estimator 406 Section 9.2: Estimating a Population Proportion—Margin of Error 410 Section 9.3: A Large Sample Confidence Interval for a Population Proportion 417 Section 9.4: Choosing a Sample Size to Achieve a Desired Margin of Error 430 Section 9.5: Avoid These Common Mistakes 433 Chapter Activities 435 Exploring the Big Ideas 437 Are You Ready to Move On? Chapter 9: Review Exercises 438 Technology Notes 440 Ch 10: Asking and Answering Questions About a Population Proportion 442 Preview 442 Chapter Learning Objectives 443 Preview Example: Gender Neutral? 443 Section 10.1: Hypotheses and Possible Conclusions 444 Section 10.2: Potential Errors in Hypothesis Testing 450 Section 10.3: The Logic of Hypothesis Testing—An Informal Example 455 Section 10.4: A Procedure for Carrying Out a Hypothesis Test 459 Section 10.5: Large-Sample Hypothesis Test for a Population Proportion 462 Section 10.6: Avoid These Common Mistakes 474 Chapter Activities 475 Exploring the Big Ideas 475 Are You Ready to Move On? Chapter 10: Review Exercises 476 Technology Notes 478 Ch 11: Asking and Answering Questions About the Difference Between Two Population Proportions 480 Preview 480 Chapter Learning Objectives 481 Preview Example: Cell-Phone Fundraising 481 Section 11.1: Estimating the Difference Between Two Population Proportions 482 Section 11.2: Testing Hypotheses About the Difference Between Two Population Proportions 490 Section 11.3: Avoid These Common Mistakes 499 Chapter Activities 499 Exploring the Big Ideas 500 Are You Ready to Move On? Chapter 11: Review Exercises 501 Technology Notes 501 Ch 12: Asking and Answering Questions About a Population Mean 504 Preview 504 Chapter Learning Objectives 505 Preview Example: Drive-Through Medicine 505 Section 12.1: The Sampling Distribution of the Sample Mean 506 Section 12.2: A Confidence Interval for a Population Mean 516 Section 12.3: Testing Hypotheses About a Population Mean 529 Section 12.4: Avoid These Common Mistakes 542 Chapter Activities 542 Exploring the Big Ideas 544 Are You Ready to Move On? Chapter 12: Review Exercises 544 Technology Notes 546 Ch 13: Asking and Answering Questions About the Difference Between Two Population Means 550 Preview 550 Chapter Learning Objectives 551 Preview Example: Depression and Chocolate 551 Section 13.1: Testing Hypotheses About the Difference Between Two Population Means Using Independent Samples 552 Section 13.2: Testing Hypotheses About the Difference Between Two Population Means Using Paired Samples 567 Section 13.3: Estimating the Difference Between Two Population Means 578 Section 13.4: Avoid These Common Mistakes 588 Chapter Activities 588 Exploring the Big Ideas 589 Are You Ready to Move On? Chapter 13: Review Exercises 589 Technology Notes 592 Ch 14: Learning from Experiment Data 598 Preview 598 Chapter Learning Objectives 599 Preview Example: Injecting Cement to Ease Pain? 599 Section 14.1: Variability and Random Assignment 600 Section 14.2: Testing Hypotheses About Differences in Treatment Effects 602 Section 14.3: Estimating the Difference in Treatment Effects 611 Section 14.4: Avoid These Common Mistakes 618 Chapter Activities 619 Are You Ready to Move On? Chapter 14: Review Exercises 620 Ch 15: Learning from Categorical Data 622 Preview 622 Chapter Learning Objectives 623 Preview Example: Is a Baseball Game Really Over by the Seventh Inning? 623 Section 15.1: Chi-Square Tests for Univariate Categorical Data 624 Section 15.2: Tests for Homogeneity and Independence in a Two-Way Table 638 Section 15.3: Avoid These Common Mistakes 653 Chapter Activities 653 Are You Ready to Move On? Chapter 15: Review Exercises 654 Technology Notes 657 Appendix A: Statistical Tables 662 Answers 675 Index 717 WCN:,02-200-203 Overview -- Section I Collecting Data -- Chapter 1 Collecting data in reasonable ways -- Section II Describing Data Distributions -- Chapter 2 Graphical methods for describing data distributions -- Chapter 3 Numerical methods for describing data distributions -- Chapter 4 Describing bivariate numerical data -- Section III A Foundation for Inference: Reasoning About Probability -- Chapter 5 Probability -- Chapter 6 Random variables and probability distributions -- Section IV Learning from Sample Data -- Chapter 7 An overview of statistical inference- learning from data -- Chapter 8 Sampling variability and sampling distributions -- Chapter 9 Estimating a population proportion -- Chapter 10 Asking and answering questions about a population proportion -- Chapter 11 Asking and answering questions about the difference between two population proportions -- Chapter 12 Asking and answering questions about a population mean -- Chapter 13 Asking and answering questions about the difference between two population means -- Section V Additional Opportunities to Learn from Data -- Chapter Learning from experiment data -- Chapter Learning from categorical data -- Chapter 16 Understanding relationships- numerical data part 2 (online) -- Chapter 17 Asking and answering questions about more than two means. STATISTICS: LEARNING FROM DATA, by respected and successful author Roxy Peck, resolves common problems faced by learners of elementary statistics with an innovative approach. Peck tackles the areas learners struggle with most--probability, hypothesis testing, and selecting an appropriate method of analysis--unlike any book on the market. Probability coverage is based on current research that shows how users best learn the subject. Two unique chapters, one on statistical inference and another on learning from experiment data, address two common areas of confusion: choosing a particular inference method and using inference methods with experimental data. Supported by learning objectives, real-data examples and exercises, and technology notes, this brand new book guides readers in gaining conceptual understanding, mechanical proficiency, and the ability to put knowledge into practice.-- Provided by Publisher