Mind on Statistics

ISBN-10: 0538733489

ISBN-13: 9780538733489

Edition: 4th 2012

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Book details

List price: $199.95
Edition: 4th
Copyright year: 2012
Publisher: Brooks/Cole
Publication date: 1/7/2011
Binding: Hardcover
Pages: 752
Size: 8.50" wide x 11.00" long x 1.25" tall
Weight: 4.136
Language: English

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.

Statistics Success Stories And Cautionary Tales
What Is Statistics?
Eight Statistical Stories with Morals
The Common Elements in the Eight Stories
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
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
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
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
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
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
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
Understanding Sampling Distributions: Statistics As Random Variables
Parameters, Statistics, and Statistical Inference
From Curiosity to Questions About Parameters
An Overview of Sampling Distributions
Sampling Distribution for One Sample Proportion
Sampling Distribution for the Difference in Two Sample Proportions
Sampling Distribution for One Sample Mean
Sampling Distribution for the Sample Mean of Paired Differences
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
Estimating Proportions With Confidence
An Overview of Confidence Intervals
Confidence Interval for a Population Proportion
Confidence Intervals for the Difference in Two Population Proportions
Using Confidence Intervals to Guide Decisions
Estimating Means With Confidence
Introduction to Confidence Intervals for Means
Confidence Interval for One Population Mean
Confidence Interval for the Population Mean of Paired Differences
Confidence Interval for the Difference in Two Population Means (Independent Samples)
Understanding Any Confidence Interval
Skillbuilder Applet: The Confidence Level in Action
Testing Hypotheses About Proportions
An Overview of Hypothesis Testing
Testing Hypotheses About a Population Proportion
Testing Hypotheses About the Difference in Two Population Proportions
Sample Size, Statistical Significance, and Practical Importance
Testing Hypotheses About Means
Introduction to Hypothesis Tests for Means
Testing Hypotheses about One Population Mean
Testing Hypotheses about the Population Mean of Paired Differences
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
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
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
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
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
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