Higher Education

# Just the Essentials of Elementary Statistics, 10th Edition

• Robert R. Johnson Monroe Community College
• Patricia J. Kuby Monroe Community College
• ISBN-10: 0495418358  |  ISBN-13: 9780495418351
• Previous Editions: 2005, 2003, 1999
• College Bookstore Wholesale Price = \$163.50

### Overview

In their own classrooms, through their popular texts, and in the conferences they lead, Bob Johnson and Pat Kuby have inspired hundreds of thousands of students and their instructors to see the utility and practicality of statistics. Robert Johnson and Patricia Kuby's ELEMENTARY STATISTICS, Tenth Edition has been consistently praised by users and reviewers for its clear exposition and relevant examples, exercises, and applications. Technology enhancements include the addition of Video Skillbuilders and StatisticsNow™ (part of the CengageNOW suite of technology products), our personalized online learning companion. This increased focus on technology to help students succeed, along with the wealth of instructor supplements and flexibility of technology coverage (with MINITAB, Excel, and TI-83 output and instructions throughout) clearly differentiate this text from its competitors as the most accessible text for students to learn from and the most straightforward text for instructors to teach from. This edition is the first 11 chapters of the parent book Elementary Statistics 10e.

Part I: DESCRIPTIVE STATISTICS.
1. Statistics.
Americans, Here''s Looking At You. What is Statistics? Measurability and Variability. Data Collection. Comparison of Probability and Statistics. Statistics and Technology.
2. Descriptive Analysis and Presentation of Single-Variable Data.
You and the Internet. Graphical Presentation of Data. Graphs, Pareto Diagrams, and Stem-And-Leaf Displays. Frequency Distributions and Histograms. Numerical Descriptive Statistics. Measures of Central Tendency. Measures of Dispersion. Measures of Position. Interpreting and Understanding Standard Deviation. The Art of Statistical Deception. Mean and Standard Deviation of Frequency Distribution (Optional).
3. Descriptive Analysis and Presentation of Bivariate Data.
The Kid is All Grown Up. Bivariate Data. Linear Correlation. Linear Regression.
Part II: PROBABILITY.
4. Probability.
Sweet Statistics. Probability of Events. Conditional Probability of Events. Rules of Probability. Mutually Exclusive Events. Independent Events. Mutually Exclusive, Independent Events—A Relationship?
5. Probability Distributions (Discrete Variables).
Caffeine Drinking. Random Variables. Probability Distribution of a Discrete Random Variable. Mean and Variance of a Discrete Probability Distribution. The Binomial Probability Distribution. Mean and Standard Deviation of the Binomial Distribution.
6. Normal Probability Distributions.
Intelligence Scores. Normal Probability Distributions. The Standard Normal Distribution. Applications of Normal Distributions. Notation. Normal Approximation of the Binomial.
7. Sample Variability.
275 Million Americans. Sampling Distributions. The Sampling Distribution of Sample Means. Application of the Sampling Distribution of Sample Means.
Part III: INFERENTIAL STATISTICS.
8. Introduction to Statistical Inferences.
Were They Shorter Back Then? The Nature of Estimation. Estimation of a Mean (ó known). The Nature of Hypothesis Testing. Hypothesis Test of Mean ì (ó Known): A Probability Value Approach. Hypothesis Test of Mean ì (ó Known): A Classical Approach.
9. Inferences Involving One Population.
Get Enough Daily Exercise? Inferences About Mean ì (ó Unknown). Inferences About the Binomial Probability of Success. Inferences About Variance and Standard Deviation.
10. Inferences Involving Two Populations.
Students, Credit Cards and Debt. Independent and Dependent Samples. Inferences Concerning the Mean Difference Using Two Dependent Samples. Inferences Concerning the Difference Between Means Using Two Independent Samples. Inferences Concerning the Difference Between Proportions Using Two Independent Samples. Inferences Concerning the Ratio of Variances Using Two Independent Samples.
Part IV: MORE INFERENTIAL STATISTICS.
11. Applications of Chi-Square.
Cooling a Great Hot Taste. Chi-Square Statistic. Inferences Concerning Multinomial Experiments. Inferences Concerning Contingency Tables.

### What's New

• The new introductory concepts, review lessons, and solutions located in the back of the text written by author, Patricia Kuby, provide your students with the help they need to grasp various algebraic and basic statistical concepts.
• StatisticsNow™ (part of the CengageNOW suite of technology products). Featured within chapters, StatisticsNow is a robust, personalized online learning companion that helps students gauge their own unique study needs and makes the most of their study time by building focused Personalized Learning Plans that reinforce key concepts. Pre-Tests give students an initial assessment of their knowledge. Personalized Learning Plans, based on the students' answers to the pre-test questions, outline key elements for review. Post-Tests assess students' mastery of core concepts for each chapter. Access to StatisticsNow is available at no additional charge with purchase of a new text.
• Interactive Video Skillbuilders contain hours of helpful, interactive video instruction. These videos walk your students through key examples from the text, step by step�giving them a foundation in the skills that they need to know. Video icons located in the margin guide students to view the video on the Skillbuilder CD-ROM.
• New technology output has been added throughout the text, reflecting the latest changes to MINITAB, Excel, and TI-83/84 graphing calculator output.
• 30% of the exercises are new and many others have been significantly updated.
• Additional critical thinking exercises have been infused throughout the exercise sets. In addition, Classic Exercises can still be found on the CD-ROM accompanying the text, providing more opportunity to assign practice exercises.
• Chapter 1 has been updated and now places a greater emphasis on interpretation of statistical information when learning key statistical terms and procedures.
• Chapter 4 on probability has been completely revised and now focuses more on analysis as opposed to formula. This is designed to increase student interest and comprehension of this sometimes difficult topic.

## Meet the Author

### Robert R. Johnson

Robert R. Johnson is Professor of Mathematics Emeritus and a former chair of the Mathematics Department at Monroe Community College. He received his B.S. from SUNY Cortland and his M.A. from University of Northern Iowa, both in mathematics; and has studied statistics at University of Iowa and Rochester Institute of Technology. Bob was the author of ELEMENTARY STATISTICS and JUST THE ESSENTIALS OF STATISTICS until being joined by co-author Patricia Kuby. They also co-author STAT. Professor Johnson has given several presentations about the "teaching of statistics" and the use of MINITAB® in teaching statistics at various conferences and workshops. He used computers and MINITAB for over 30 years to aid in teaching statistics. He was also an active advocate for writing across the curriculum. Organizing the Beyond the Formula Statistics Conferences for teachers of Introductory Statistics was a passion from 1997 through 2005.

### Patricia J. Kuby

Patricia J. Kuby is Professor of Mathematics at Monroe Community College in Rochester, New York. Prior to coming to MCC, she taught at the Rochester Institute of Technology and worked as a statistician and programmer at General Motors. Patricia has been a co-author of ELEMENTARY STATISTICS since the eighth edition, JUST THE ESSENTIALS OF ELEMENTARY STATISTICS since the ninth edition and STAT. She has also written the accompanying Instructor’s Resource Manuals and Student Solutions Manuals. Patricia is an active advocate for incorporating MINITAB® and Interactive Applets into online and on-campus statistics classes and has given presentations on each of these software packages, as well as the integration of a Student Response System (clickers) in a statistics class. While at RIT, Patricia received the Excellence in Adjunct Teaching Award. She also received the Monroe Community College 2004/2005 Writing Across the Curriculum Outstanding Faculty Award for the integration of writing components into her statistics courses and the 2007/2008 SUNY Chancellor’s Award for Excellence in Teaching. An MCC graduate, Patricia received a B.S. in Mathematics and an M.S. in Quality and Applied Statistics from Rochester Institute of Technology.