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Mind on Statistics

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ISBN-10: 0534393055

ISBN-13: 9780534393052

Edition: 2nd 2004

Authors: Jessica M. Utts, Robert F. Heckard

List price: $316.95
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Emphasizing the conceptual development of statistical ideas, MIND ON STATISTICS actively engages students and explains topics in the context of excellent examples and case studies. This text balances the spirit of statistical literacy with statistical methodology taught in the introductory statistics course. Jessica Utts and Robert Heckard built the book on two learning premises: (1) New material is much easier to learn and remember if it is related to something interesting or previously known; (2) New material is easier to learn if you actively ask questions and answer them for yourself. More than any other text available, MIND ON STATISTICS motivates students to develop their statistical…    
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Book details

List price: $316.95
Edition: 2nd
Copyright year: 2004
Publisher: Brooks/Cole
Publication date: 5/29/2003
Binding: Hardcover
Pages: 610
Size: 8.25" wide x 10.25" long x 1.00" tall
Weight: 3.036

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…    

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? Seven Statistical Stories with Morals
Who Are Those Speedy Drivers?
Safety in the Skies
Did Anyone Ask You Whom You've Been Dating?
Who Are Those Angry Women?
Does Prayer Lower Blood Pressure?
Does Aspirin Reduce Heart Attack Rates?
Does the Internet Increase Loneliness and Depression? The Common Elements of the Seven Stories
Turning Data Into Information
Raw Data
Types of Variables
Summarizing One or Two Categorical Variables
Exploring Features of Quantitatve Data with Pictures
Numerical Summaries of Quantitative Variables
How to Handle Outliers
Features of Bell-Shaped Distributions
Skillbuilder Applet: The Empirical Rule in Action
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
The Infamous Literary Digest Poll of
1936 How to Ask Survey Questions
No Opinion of Your Own? Let Politics Decide
Skillbuilder Applet: Random Sampling in Action
Gathering Useful Data For Examining Relationships
Speaking the Language of Research Studies
Lead Exposure and Bad Teeth
Designing a Good Experiment
Kids and Weight Lifting
Quitting Smoking with Nicotine Patches
Designing a Good Observational Study
Baldness and Heart Attacks
Difficulties and Disasters in Experiments and Observational Studies
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
A Weighty Issue
Relationships Between Categorical Variables
Displaying Relationships Between Categorical Variables
Risk, Relative Risks, and Misleading Statistics About Risk
Is Smoking More Dangerous for Women?
The Effect of a Third Variable and Simpson's Paradox
Assessing the Statistical Significance of a 2 x 2 Table
Drinking, Driving, and the Supreme Court
Random Circumstances
A Hypothetical Story--Alicia Has a Bad Day
Interpretations of Probability
Probability Definitions and Relationships
Basic Rules for Finding Probabilities
Strategies for Finding Complicated Probabilities
Using Simulation to Estimate Probabilities
Coincidences and Intuitive Judgments About Probability
Doin' the iPod Shuffle
Random Variables
What is a Random Variable? Discrete Random Variables
Expectations for Random Variables
Binomial Random Variables
Does Caffeine Enhance the Taste of Cola? 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
Standardized Statistics for Sampling Distributions
Standardized Statistics for Proportions
Standardized Statistics for Means
Generalizations Beyond the Big Five
Skillbuilder Applet: Finding the Pattern in Sample Means
Do Americans Really Vote When They Say They Do? Table: Summary of Sampling Distributions
Estimating Proportions With Confidence
An Overview of Confidence Intervals
Understanding Confidence Intervals
Computing Confidence Intervals for the Five Scenarios
Confidence Interval for a Population Proportion
Details of How to Compute a Confidence Interval for a Population Proportion
Understanding the Formula
Reconciling Margin of Error and 95% Confidence Intervals
Confidence Intervals for the Difference in Two Population Proportions
Using Confidence Intervals to Guide Decisions
Extrasensory Perception Works With Movies
Nicotine Patches Versus Zyban
What a Great Personality
Estimating Means With Confidence
Introduction to Confidence Intervals for Means
Confidence Intervals for One Population Mean
Finding a Confidence Interval for a Mean For Any Sample Size and Any Confidence Level
Special Case: Approximate 95% Confidence Intervals for Large Samples
Confidence Interval for the Population Mean of Paired Differences
Confidence Interval for the Difference in Two Population Means
The General (Unpooled) Case
The Equal Variance Assumption and the Pooled Standard Error
Understanding Any Confidence Interval
Confidence Interval for Relative Risk: Case Study 4.4 Revisited
Premenstrual Syndrome? Try Calcium
Skillbuilder Applet: The Confidence Level in Action
Table: Summary of Confidence Interval Procedures
Testing Hypotheses About Proportions
An Overview of Hypothesis Testing
Formulating Hypothesis Statements
The Logic and Details of Hypothesis Testing
What Can Go Wrong: The Two Types of Errors and Their Probabilities
Testing Hypotheses about a Population Proportion
Testing Hypotheses about the Difference in Two Population Proportions
Sample Size, Statistical Significance and Practical Importance
The Internet and Loneliness: Case Study 1.7 Revisited
An Interpretation of a p-Value Not Fit to Print
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
The General (Unpooled) Case
The Pooled Two-Sample t-Test
The Relationship Between Significance Tests and Confidence Intervals
Choosing an Appropriate Inference Procedure
Effect Size
Evaluating Significance in Research Reports
Table: Summary of Hypothesis Testing Procedures
Inference About Simple Regression
Sample and Population Regression Models
Estimating the Standard Deviation for Regression
Inference About the Linear Regression Relationship
Predicting y and Estimating Mean y at a Specific X
Checking Conditions for Using Regression Models for Inference
A Contested Election
More Inference About Categorical Variables
The Chi-Square Test for Two-Way Tables
Analyzing 2 x 2 Tables
Testing Hypotheses About One Categorical Variable: Goodness of Fit
Do You Mind if I Eat the Blue Ones?
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
Appendix of Tables
Answers to Selected Exercises
Supplemental Topics (Appear On The Student Suite Cd-Rom Only)
Additional Discrete Random Variables
Hypergeometric Distribution
Poisson Distribution
Multinomial Distribution
Nonparametric Tests Of Hypotheses
The Sign Test
The Two-Sample Rank-Sum Test
The Wilcoxon Signed-Rank Test
The Kruskal-Wallis Test
Multiple Regression
The Multiple Linear Regression Model
Inference About Multiple Regression Models
Checking Conditions for Multiple Linear Regression
Two-Way Analysis of Variance
Assumptions and Models for Two-Way ANOVA
Testing for Main Effects and Interactions
Ethical Treatment of Human and Animal Participants
Assurance of Quality Data
Appropriate Statistical Analysis
Fair Reporting of Results
Case Study S5.1: Science Fair Project or Fair Science Project.