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MIND ON STATISTICS emphasizes the conceptual development of statistical ideas and the importance of looking for--and finding--meaning in data. Authors Jessica Utts and Robert Heckard actively engage students' natural curiosity, motivating them with intriguing questions and explaining statistical topics in the context of a wide range of interesting, useful examples and case studies. Throughout, the authors balance the promotion of statistical literacy with coverage of the statistical methodology taught in general introductory statistics courses. Their approach is based on the premises that new material is much easier to learn and remember if it is related to something interesting or previously known, and if students actively ask questions and find the answers for themselves. More than any other text available, MIND ON STATISTICS motivates and encourages students to develop their statistical intuition by focusing on analyzing data and interpreting results, rather than on mathematical formulation.
- To create a more natural flow of topic coverage, Chapters 5 and 6 have been moved to precede Chapters 3 and 4 so that the material on describing data comes before the two chapters on collecting data.
- The language has been tightened and simplified in all chapters whenever possible. In particular, Chapters 9, 10, and 12 have been substantially honed.
- New topics in this edition include multiple comparisons in Chapters 1 and 13, power curves in Chapters 12 and 13, and McNemar's test in Chapter 15.
- The exercise sets have been significantly reorganized and rewritten. For example, in response to reviewers' suggestions, many exercises are now set up in odd-even pairs, featuring odd-numbered problems--which are answered in the back of the book--followed by similar even-numbered problems. In addition, a number of new problems have been added, including a significant number of new drill exercises.
- The data in the problem sets, examples, and case studies have been updated with the latest possible information. In addition, the book includes all-new examples and case studies as well as new and updated data sets.
- A greater number of In Summary boxes are placed consistently throughout each chapter, reinforcing key ideas as students read. A listing of the In Summary boxes now appears at the end of the chapter, making these features even more helpful as study aids.
- Aplia™ is available with the new edition. This online interactive learning solution--which improves student comprehension and outcomes with detailed, immediate explanations--also saves you time by automatically grading assignments.
- Original journal articles for selected case studies and examples (identified in the text by an icon) can be found on the book's website, Statistics CourseMate. Reading these original articles enables students to learn more about how the research was conducted, what methods were used, and the conclusions drawn.
- Compelling examples and "real-life" case studies help to motivate and engage students in statistical topics, reinforcing the text's premise that material is easier to learn if it can be related to something interesting or previously learned.
- The book helps students expand their "frame of reference" with unique and motivating opening and closing chapters that draw them into the subject matter. These chapters clearly illustrate how statistical methods have contributed to our understanding of health, psychology, commerce, ecology, politics, music, lifestyle choices, and dozens of other topics.
- Thought Questions, along with hints on how to solve them, provide students with opportunities to explore a topic further--and discover and verify important ideas for themselves. Complete answers are available on the instructor PowerLecture™ CD-ROM.
- Complementing the technology-specific Technical Tips, more general Technical Notes provide additional discussion on statistical techniques presented in the text; for instance, Summarizing Ordinal Variables and Population Mean and Standard Deviation.
- In Summary boxes appear at points within the chapter where students need them most, as opposed to being relegated to the end of a chapter or section.
- Skillbuilder Applet activities, found throughout the text, use Java™ applets from CyberStats to explore key statistical topics. These applets, which are on the book's companion website, Statistics CourseMate, give students opportunities for hands-on learning and allow them to explore statistics on their own. Skillbuilder Applet Exercises at the end of the chapters make the applets easy to integrate into your teaching.
- Chapters 9–13, containing the core material on sampling distributions and statistical inference, are organized in a modular, flexible format. There are six modules for each of the topics of sampling distributions, confidence intervals, and hypothesis testing. The first module provides an introduction and each of the remaining five modules deals with a specific parameter (one mean, one proportion, etc.). This modular format emphasizes the similarity among the inference procedures for the five parameters discussed, and allows instructors to cover this material in any order they choose.
- Technology Tips appear throughout the text for MINITAB®, SPSS®, Excel®, JMP, and TI-83/84 calculators. Technical manuals for these technologies, as well as for JMP and R, are available on the book's website, Statistics CourseMate.
What Is Statistics? Eight Statistical Stories with Morals. The Common Elements in the Eight Stories.
2. TURNING DATA INTO INFORMATION.
Raw Data. Types of Variables. Summarizing One or Two Categorical Variables. Exploring Features of Quantitative Data with Pictures. Numerical Summaries of Quantitative Variables. How to Handle Outliers. Bell-Shaped Distributions and Standard Deviations. Skillbuilder Applet: The Empirical Rule in Action.
3. RELATIONSHIPS BETWEEN QUANTITATIVE VARIABLES.
Looking for Patterns with Scatterplots. Describing Linear Patterns with a Regression Line. Measuring Strength and Direction with Correlation. Regression and Correlation Difficulties and Disasters. Correlation Does Not Prove Causation. Skillbuilder Applet: Exploring Correlation.
4. RELATIONSHIPS BETWEEN CATEGORICAL VARIABLES.
Displaying Relationships Between Categorical Variables. Risk, Relative Risk, and Misleading Statistics About Risk. The Effect of a Third Variable and Simpson''s Paradox. Assessing the Statistical Significance of a 2 x 2 Table.
5. SAMPLING: SURVEYS AND HOW TO ASK QUESTIONS.
Collecting and Using Sample Data Wisely. Margin of Error, Confidence Intervals, and Sample Size. Choosing a Simple Random Sample. Other Sampling Methods. Difficulties and Disasters in Sampling. How to Ask Survey Questions. Skillbuilder Applet: Random Sampling in Action.
6. GATHERING USEFUL DATA FOR EXAMINING RELATIONSHIPS.
Speaking the Language of Research Studies. Designing a Good Experiment. Designing a Good Observational Study. Difficulties and Disasters in Experiments and Observational Studies.
Random Circumstances. Interpretations of Probability. Probability Definitions and Relationships. Basic Rules for Finding Probabilities. Finding Complicated Probabilities. Using Simulation to Estimate Probabilities. Flawed Intuitive Judgments About Probability.
8. RANDOM VARIABLES.
What Is a Random Variable? Discrete Random Variables. Expectations for Random Variables. Binomial Random Variables. Continuous Random Variables. Normal Random Variables. Approximating Binomial Distribution Probabilities. Sums, Differences, and Combinations of Random Variables.
9. UNDERSTANDING SAMPLING DISTRIBUTIONS: STATISTICS AS RANDOM VARIABLES.
Parameters, Statistics, and Statistical Inference. From Curiosity to Questions About Parameters. SD Module 0: An Overview of Sampling Distributions. SD Module 1: Sampling Distribution for One Sample Proportion. SD Module 2: Sampling Distribution for the Difference in Two Sample Proportions. SD Module 3: Sampling Distribution for One Sample Mean. SD Module 4: Sampling Distribution for the Sample Mean of Paired Differences. SD Module 5: Sampling Distribution for the Difference in Two Sample Means. Preparing for Statistical Inference: Standardized Statistics. Generalizations Beyond the Big Five. Skillbuilder Applet: Finding the Pattern in Sample Means.
10. ESTIMATING PROPORTIONS WITH CONFIDENCE.
CI Module 0: An Overview of Confidence Intervals. CI Module 1: Confidence Interval for a Population Proportion. CI Module 2: Confidence Intervals for the Difference in Two Population Proportions. Using Confidence Intervals to Guide Decisions.
11. ESTIMATING MEANS WITH CONFIDENCE.
Introduction to Confidence Intervals for Means. CI Module 3: Confidence Interval for One Population Mean. CI Module 4: Confidence Interval for the Population Mean of Paired Differences. CI Module 5: Confidence Interval for the Difference in Two Population Means (Independent Samples). Understanding Any Confidence Interval. Skillbuilder Applet: The Confidence Level in Action.
12. TESTING HYPOTHESES ABOUT PROPORTIONS.
HT Module 0: An Overview of Hypothesis Testing. HT Module 1: Testing Hypotheses About a Population Proportion. HT Module 2: Testing Hypotheses About the Difference in Two Population Proportions. Sample Size, Statistical Significance, and Practical Importance.
13. TESTING HYPOTHESES ABOUT MEANS.
Introduction to Hypothesis Tests for Means. HT Module 3: Testing Hypotheses about One Population Mean. HT Module 4: Testing Hypotheses about the Population Mean of Paired Differences. HT Module 5: Testing Hypotheses about the Difference in Two Population Means (Independent Samples). The Relationship Between Significance Tests and Confidence Intervals. Choosing an Appropriate Inference Procedure. Effect Size. Evaluating Significance in Research Reports.
14. INFERENCE ABOUT SIMPLE REGRESSION.
Sample and Population Regression Models. Estimating the Standard Deviation for Regression. Inference About the Slope of a Linear Regression. Predicting y and Estimating Mean y at a Specific x. Checking Conditions for Using Regression Models for Inference.
15. MORE ABOUT INFERENCE FOR CATEGORICAL VARIABLES.
The Chi-Square Test for Two-Way Tables. Analyzing 2 x 2 Tables. Testing Hypotheses About One Categorical Variable: Goodness-of-Fit.
16. ANALYSIS OF VARIANCE.
Comparing Means with an ANOVA F-Test. Details of One-Way Analysis of Variance. Other Methods for Comparing Populations. Two-Way Analysis of Variance.
17. TURNING INFORMATION INTO WISDOM.
Beyond the Data. Transforming Uncertainty Into Wisdom. Making Personal Decisions. Control of Societal Risks. Understanding Our World. Getting to Know You. Words to the Wise.
Cengage provides a range of supplements that are updated in coordination with the main title selection. For more information about these supplements, contact your Learning Consultant.
This online instructor database offers complete worked solutions to all exercises in the text, allowing you to create customized, secure solutions printouts (in PDF format) matched exactly to the problems you assign in class. http://www.cengage.com/solutionbuilder.
Student Solutions Manual
Contains fully worked-out solutions to all of the odd-numbered exercises in the text, giving students a way to check their answers and ensure that they took the correct steps to arrive at an answer.
Online Activities Workbook
Online activity workbook
Student Solutions Manual
Go beyond the answers—see what it takes to get there and improve your grade! This manual provides worked-out, step-by-step solutions to the odd-numbered problems in the text, giving you the information you need to truly understand how these problems are solved.
Online Activities Workbook
Online activity workbook