Student Solutions Manual for Stats

Description

Reflects the new Guidelines for Assessment and Instruction in Statistics Education (GAISE) 2016 report adopted by the American Statistical Association to encourage statistical thinking

• New – Random Matters: This new feature encourages a gradual, cumulative understanding of randomization. The first Random Matters box introduces drawing inferences from data. Subsequent Random Matters features draw histograms of sample means, introduce the thinking involved in permutation tests, and encourage judgment about how likely the observed statistic seems when viewed against the simulated sampling distribution of the null hypothesis.
• New –  Streamlined coverage of descriptive statistics helps students progress more quickly through the first part of the book. Also a GAISE recommendation, random variables and probability distributions are now covered later in the text to allow for more time on the more critical statistical concepts.
• New – Technology is utilized to improve the learning of two of the most difficult concepts in the introductory course: the idea of a sampling distribution and the reasoning of statistical inference.
• New –  A third variable is introduced with contingency tables and mosaic plots in Chapter 3 to give students earlier experience with multivariable thinking. Then, following the discussion of correlation and regression as a tool (without inference) in Chapters 6, 7, and 8, multiple regression is introduced in Chapter 9.
• Where Are We Going? chapter openers give a context for the work students are about to begin within the broader course.
• Margin and in-text boxed notes throughout each chapter enhance and enrich the text.
• Reality Checks ask students to think about whether their answers make sense before interpreting their results.
• Notation Alerts appear whenever special notation is introduced.

• The Tech Support section provides instructions for applying the topics covered by the chapter within each of the supported statistics packages.

Supports learning through worked examples and practice opportunities

• Updated –  Expanded and revised Think/Show/Tell Step-by-Step Examples guide students through the process of analyzing a problem through worked examples. They illustrate the importance of thinking about a statistics question (Think) and reporting findings (Tell)). The Show step contains the mechanics of calculating results. This results in a better understanding of the concept and problem-solving process that goes beyond number crunching.
• Focused examples are provided as each important concept is introduced, applying the concept usually with real, up-to-the-minute data. Many examples carry the discussion through the chapter, picking up the story and moving it forward as students learn more about the topic.
• Just Checking questions are quick checks throughout the chapter that involve minimal calculation and encourage students to pause and think about what they’ve just read. The Just Checking answers are at the end of the exercise sets in each chapter so students can easily check themselves.
• End-of-chapter material includes:
• Connections sections that specifically ties the new topics to those learned in previous chapters.
• What Can Go Wrong? sections that highlight the most common errors that people make and the misconceptions they have about statistics. One of our goals is to arm students with the tools to detect statistical errors and to offer practice in debunking misuses of  statistics., whether intentional or not.
• Chapter Reviews that summarize the story told by the chapter and provide a bulleted lists of the major concepts and principles covered.
• A Review of Terms glossary of all of the boldfaced terms introduced in the chapter. The Review provides page references, so students can easily turn back to a full discussion of the term if the brief definition isn’t sufficient.

• Abundant exercises at the end of each chapter start with relatively simple, focused exercises for each chapter section and move on to more extensive exercises that may deal with topics from several parts of the chapter or even from previous chapters as they combine with the topics of the chapter at hand. All exercises appear in pairs, and odd-numbered exercises have answers in the back of student texts. Each even-numbered exercise covers the same topic (although not in exactly the same way) as the previous odd exercise.
• More than 600 of the exercises include an icon indicating that the dataset referenced is available electronically. The exercise title or a note provides the dataset title. Some exercises are tagged to indicate that they call for the student to generate random samples or use randomization methods such as the bootstrap.

• Part Reviews discuss the concepts in each part of the text, tying them together and summarizing the material.
• Additional exercises follow the Part Reviews; these are not paired and not tied to a chapter, making them more like potential exam questions and a good tool for review.
• Parts I-V Cumulative Review Exercises comprise a final book-level review section towards the end of the text. Cumulative Review exercises are longer and cover concepts from the book as a whole.
• New – Web tools provide interactive versions of the distribution tables at the back of the book and tools for randomization inference methods such as the bootstrap and for repeated sampling from larger populations can be found online at astools.datadesk.com.

Richard D. De Veaux is an internationally known educator and consultant. He has taught at the Wharton School and the Princeton University School of Engineering, where he won a “Lifetime Award for Dedication and Excellence in Teaching.” He is the C. Carlisle and M. Tippit Professor of Statistics at Williams College, where he has taught since 1994. Dick has won both the Wilcoxon and Shewell awards from the American Society for Quality. He is a fellow of the American Statistical Association (ASA) and an elected member of the International Statistical Institute (ISI). In 2008, he was named Statistician of the Year by the Boston Chapter of the ASA. Dick is also well known in industry, where for more than 30 years he has consulted for such Fortune 500 companies as American Express, Hewlett-Packard, Alcoa, DuPont, Pillsbury, General Electric, and Chemical Bank. Because he consulted with Mickey Hart on his book Planet Drum, he has also sometimes been called the “Official Statistician for the Grateful Dead.” His real-world experiences and anecdotes illustrate many of this book’s chapters.

Dick holds degrees from Princeton University in Civil Engineering (B.S.E.) and Mathematics (A.B.) and from Stanford University in Dance Education (M.A.) and Statistics (Ph.D.), where he studied dance with Inga Weiss and Statistics with Persi Diaconis. His research focuses on the analysis of large data sets and data mining in science and industry.

In his spare time, he is an avid cyclist and swimmer. He also is the founder of the “Diminished Faculty,” an a cappella Doo-Wop quartet at Williams College, and sings bass in the college concert choir and with the Choeur Vittoria of Paris. Dick is the father of four children.

Paul F. Velleman has an international reputation for innovative Statistics education. He is the author and designer of the multimedia Statistics program ActivStats, for which he was awarded the EDUCOM Medal for innovative uses of computers in teaching statistics, and the ICTCM Award for Innovation in Using Technology in College Mathematics. He also developed the award-winning statistics program Data Desk, and the Internet site Data and Story Library (DASL) (ASL.datadesk.com), which provides data sets for teaching Statistics. Paul’s understanding of using and teaching with technology informs much of this book’s approach.

Paul has taught Statistics at Cornell University since 1975, where he was awarded the MacIntyre Award for Exemplary Teaching. He holds an A.B. from Dartmouth College in Mathematics and Social Science, and M.S. and Ph.D. degrees in Statistics from Princeton University, where he studied with John Tukey. His research often deals with statistical graphics and data analysis methods. Paul co-authored (with David Hoaglin) ABCs of Exploratory Data Analysis. Paul is a Fellow of the American Statistical Association and of the American Association for the Advancement of Science. Paul is the father of two boys.

David E. Bock taught mathematics at Ithaca High School for 35 years. He has taught Statistics at Ithaca High School, Tompkins-Cortland Community College, Ithaca College, and Cornell University. Dave has won numerous teaching awards, including the MAA’s Edyth May Sliffe Award for Distinguished High School Mathematics Teaching (twice), Cornell University’s Outstanding Educator Award (three times), and has been a finalist for New York State Teacher of the Year.

Dave holds degrees from the University at Albany in Mathematics (B.A.) and Statistics/Education (M.S.). Dave has been a reader and table leader for the AP Statistics exam, serves as a Statistics consultant to the College Board, and leads workshops and institutes for AP Statistics teachers. He has served as K–12 Education and Outreach Coordinator and a senior lecturer for the Mathematics Department at Cornell University. His understanding of how students learn informs much of this book’s approach.

Dave and his wife relax by biking or hiking, spending much of their free time in Canada, the Rockies, or the Blue Ridge Mountains. They have a son, a daughter, and four grandchildren.

Reflects the new Guidelines for Assessment and Instruction in Statistics Education (GAISE) 2016 report adopted by the American Statistical Association to encourage statistical thinking

• Random Matters – This new feature encourages a gradual, cumulative understanding of randomization. The first Random Matters box introduces drawing inferences from data. Subsequent Random Matters features draw histograms of sample means, introduce the thinking involved in permutation tests, and encourage judgment about how likely the observed statistic seems when viewed against the simulated sampling distribution of the null hypothesis.

• Streamlined coverage of descriptive statistics helps students progress more quickly through the first part of the book. Also a GAISE recommendation, random variables and probability distributions are now covered later in the text to allow for more time on the more critical statistical concepts.

• Technology is utilized to improve the learning of two of the most difficult concepts in the introductory course: the idea of a sampling distribution and the reasoning of statistical inference.

Supports learning through worked examples and practice opportunities

• A third variable is introduced with contingency tables and mosaic plots in Chapter 3 to give students earlier experience with multivariable thinking. Then, following the discussion of correlation and regression as a tool (without inference) in Chapters 6, 7, and 8, multiple regression is introduced in Chapter 9.

• Expanded and revised Think/Show/Tell Step-by-Step Examples guide students through the process of analyzing a problem through worked examples. They illustrate the importance of thinking about a statistics question (Think) and reporting findings (Tell)). The Show step contains the mechanics of calculating results. This results in a better understanding of the concept and problem-solving process that goes beyond number crunching.

• New Web tools that provide interactive versions of the distribution tables at the back of the book and tools for randomization inference methods such as the bootstrap and for repeated sampling from larger populations can be found online at astools.datadesk.com.

Additional information

Dimensions	0.95 × 8.50 × 10.75 in
Imprint	Pearson
Format	gen
ISBN-13	09780135163979
ISBN-10	0135163978
Author	David E. Bock, Floyd Bullard, Paul F. Velleman, Richard D. De Veaux
Subjects	statistics, mathematics, higher education, Introductory Statistics