Ebook Mind on Statistics, 4th Edition, by Jessica M. Utts, Robert F. Heckard
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Mind on Statistics, 4th Edition, by Jessica M. Utts, Robert F. Heckard
Ebook Mind on Statistics, 4th Edition, by Jessica M. Utts, Robert F. Heckard
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MIND ON STATISTICS helps you develop a conceptual understanding of statistical ideas and shows you how to find meaning in data. The authors--who are committed to changing any preconception you may have about statistics being boring--engage your curiosity with intriguing questions, and explain statistical topics in the context of interesting, useful examples and case studies. You'll develop your statistical intuition by focusing on analyzing data and interpreting results, rather than on mathematical formulation. As a result, you'll build both your statistical literacy and your understanding of statistical methodology.
- Sales Rank: #339616 in Books
- Brand: Cengage Learning
- Published on: 2011-01-07
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 1.10" h x 8.80" w x 10.80" l, 3.83 pounds
- Binding: Hardcover
- 717 pages
- Used Book in Good Condition
Review
1. STATISTICS SUCCESS STORIES AND CAUTIONARY TALES. 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. 7. PROBABILITY. 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.
About the Author
Jessica Utts is Professor of Statistics at the University of California at Irvine. She received her B.A. in math and psychology at SUNY Binghamton, and her M.A. and Ph.D. in statistics at Penn State University. Aside from MIND ON STATISTICS, she is the author of SEEING THROUGH STATISTICS and the co-author with Robert Heckard of STATISTICAL IDEAS AND METHODS both published by Cengage Learning. Jessica has been active in the Statistics Education community at the high school and college level. She served as a member and then chaired the Advanced Placement Statistics Development Committee for six years, and was a member of the American Statistical Association task force that produced the GAISE (Guidelines for Assessment and Instruction in Statistics Education) recommendations for Elementary Statistics courses. She is the recipient of the Academic Senate Distinguished Teaching Award and the Magnar Ronning Award for Teaching Excellence, both at the University of California at Davis. She is also a fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science. Beyond statistics education, Jessica's major contributions have been in applying statistics to a variety of disciplines, most notably to parapsychology, the laboratory study of psychic phenomena. She has appeared on numerous television shows, including LARRY KING LIVE, ABCNIGHTLINE, CNN MORNING NEWS, and 20/20, and most recently appears in a documentary included on the DVD with the movie SUSPECT ZERO.
Robert F. Heckard is a senior lecturer in statistics at the Pennsylvania State University, where he has taught for more than 30 years. He has taught introductory and intermediate applied statistics to more than 15,000 college students. Bob has been awarded several grants to develop multimedia and web-based instructional materials for teaching statistical concepts. Aside from MIND ON STATISTICS, he is the co-author of STATISTICAL IDEAS AND METHODS (first edition, 2006, Cengage Learning). As a consultant, he is active in the statistical analysis and design of highway safety research and has frequently been a consultant in cancer treatment clinical trials.
Most helpful customer reviews
1 of 1 people found the following review helpful.
Great conceptual explanations
By scienceguy45
This book emphasizes the concepts that underlie various statistical methods and tools rather than the formulas needed to compute various statistics and parameters. An excellent book for introducing basic statistic concepts.
0 of 0 people found the following review helpful.
It explains the topics pretty well. Sometimes you have to skip around the ...
By Rebecca Simonsick
It explains the topics pretty well. Sometimes you have to skip around the book to find the whole explaination, but it makes it easier to learn it.
0 of 0 people found the following review helpful.
helped me get a 100 :)
By casandra light
was in good condition and received it when i was supposed to definitely helped my in my biostatistics class because i got a 100 in the class :)
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