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Statistics: The Art and Science of Learning From Data
ISBN-10: 0130083690
ISBN-13: 9780130083692
Publisher: Prentice Hall
Copyright: 2007
Format: Cloth; 768 pp
Published: 01/17/2006
Status: Out of Print
Suggested retail price: $137.33
For algebra-based Introductory Statistics Courses.
The overarching goal of this text is to empower students to be statistical thinkers
Alan Agresti and Chris Franklin have merged their research expertise, as well as their extensive real-world and teaching experience, to develop a new introductory statistics text that makes students statistically literate, while encouraging them to ask and answer interesting statistical questions. The authors have successfully crafted a text that takes the ideas that have turned statistics into a central science in modern life and makes them accessible and engaging to students without compromising necessary rigor.
The varied and data-rich examples and exercises place heavy emphasis on thinking about and understanding statistical concepts. The applications are topical and current and successfully illustrate the relevance of statistics.
The authors understand that most of the real-world data that students encounter outside the class room are categorical data. Unlike many texts at this level, Agresti/Franklin incorporates categorical data where appropriate and draws distinctions between theory and practical application of statistical ideas and methods.
The text was written, from the ground up, to embrace and support the 6 recommendations of the ASA endorsed GAISE (Guidelines for Assessment for Instruction in Statistical Education) Report - http://www.amstat.org/education/gaise/GAISECollege.htm:
- Emphasize statistical literacy and develop statistical thinking.
- Use real data.
- Stress conceptual understanding rather than mere knowledge of procedures.
- Foster active learning in the classroom.
- Use technology for developing concepts and analyzing data.
- Use assessment to evaluate and improve student learning.
Comes with a CD containing data sets, additional activities, and applets. The CD with the IE, furthermore, includes Instructor-to-Instructor videos which further detail, by chapter, the authors approach and provides suggestions on how to present concepts. These Instructor-to-Instructor videos are very complimentary to the IE chapter introductions.
This text has three primary goals:
1. To empower students to think statistically by teaching them to ask and answer interesting questions.
2. Connecting statistics to the real world by offering a more balanced and parallel treatment of proportions and means, specifically by appropriately incorporating categorical data.
3. Offering clear and accessible explanations to students
In the context of achieving these goals, the authors closely adhere to the ASA endorsed GAISE recommendations ( http://www.amstat.org/education/gaise/GAISECollege.htm )
GOAL #1:
Agresti/ Franklin is written with the singular purpose of empowering students to think statistically - to ask and answer interesting questions about the data. The examples and exercises play a central role in facilitating statistical thinking.
Question:
How do you know when your students are thinking statistically? Can you tell from the types of questions they ask?
How do you encourage your students to think beyond procedures and to focus on context (i.e. what the numbers tell us)?
(A) EXAMPLES:
Questions:
1. What role do the examples in the text play in your course? What role do the examples play for your students?
2. Do your students struggle with knowing WHERE and HOW to start?
3. Are engaging examples going to motivate your students to better understand the context?
Examples emphasize thinking about and understanding statistical concepts through analysis of current, real-world data. Reviewers and students alike have identified the examples as an outstanding feature of this textbook. The examples are developed in a unique 5-step example format that encourages students to model the investigative thought process required to examine issues intelligently in statistics.
The five components are:
1. Picture the Scenario: Background information is presented so students can visualize the situation. This step places the data to be investigated in context and often provides a link back to previous examples.
2. Questions to Explore: Questions are posed that follow directly from information in the scenario. Posing questions helps the student to focus on what is to be learned from the example, where to begin and what types of questions are useful to ask about the data.
3. Think It Through: This step is the heart of each example as the questions posed are investigated and answered using appropriate statistical methods. Each solution is clearly matched to the questions so students can easily find the response to each posed Question to Explore.
4. Insight: This step clarifies the central ideas investigated in the example and places them in a broader context that often states the conclusions in less technical terms. Many of the Insights also provide connections between seemingly disparate topics in the text by referring back to concepts learned previously and /or foreshadowing techniques and ideas to come.
5. To Practice This Concept, try…: Following each example, students are directed to an end-of-section exercise that allows immediate practice of the concept.
(B) EXERCISES:
Question:
1. Is it important that the exercises ask students to interpret the data or scenario rather than merely to find a numerical solution?
Exercises motivate and test student comprehension through interesting real data problems. Students are asked to solve problems about questions including: The effects of smoking. Thechance of being audited by the IRS.The margin of error for a Gallup Poll. The impact of pollution. The public’s support for the death penalty. And myriad other thought-provoking questions.
- Practice with an extensive and diverse range of exercises – With more than 100 exercises per chapter, building in difficulty, instructors have a large variety of exercises to assign for homework. In turn, students have ample opportunity to practice the concepts presented within the chapter and foster their critical-thinking skills. Exercises ask students to provide graphs and interpretations of the data or scenario rather than merely to find a numerical solution.
- Challenge students on different levels - The exercise sets are divided into three categories:
1. Practicing the Basics: Reinforce basic application of methods.
2. Concepts and Investigations: Require students to explore the theory and concepts presented in the chapter through real data sets. Selected mini-projects offer extensions of the chapter’s core methods. This category of problems contains some multiple-choice and true/false exercises to help students check their understanding of the basic concepts and prepare for standardized tests. This category also contains many more challenging, optional exercises that present additional concepts and methods.
3. Class Explorations: Exercises and activities that are designed for individual investigation or group work.
GOAL #2:
Agresti/ Franklin connect statistics to the real world by offering a more balanced and parallel treatment of proportions and means, specifically by appropriately incorporating categorical data.
Question:
1. How do you convey and emphsize the relevance and applicability of statistics in the real world?
Opinion polls, economic reports, and medical studies typically use percentages and rates to summarize results. The analysis of these proportions is common in everyday life and is emphasized throughout the text. While methods for analyzing normally distributed and continuous data are thoroughly discussed, significant attention is paid to proportions.
- Sampling distributions and inference methods using proportions for a binary outcome are explained and then contingency tables are used to illustrate the concept of association and to show the potential influence of a lurking variable.
- Pedagogically, it is easier for a student to look first at a sample of binary data or a distribution of sample proportions with a small sample size and understand what this distribution refers to than to do the same for a bell-shaped curve for a continuum of unobserved values.
- IN PRACTICE — these marginal boxes alert students to the way statisticians actually analyze data in practice.
Valuable instructor resources are provided to support and reinforce this approach.
- Instructor to Instructor Videos and the Instructor Edition work together to further define the approach of each chapter and suggests strategies for presenting key concepts.
GOAL #3:
Offering clear and accessible explanations to students
Clarifies the content, and updates the traditional table of contents where possible, without sacrificing accuracy — Selection of topics is focused on those that are used in practice.
- For instance, a serious source of confusion for students is the large number of inference methods that result from the many different kinds of tests and conditions presented. In contrast to most texts, Agresti and Franklin place main emphasis on the most important cases for practical application of inference: large sample, variance unknown, two-sided inference, and independent samples. The many other cases are also covered (except for known variances), but more briefly.
Encourages Active Learning — To help illustrate concepts and techniques, students are directed to optional activities and applets at the appropriate times.
Technology is used to develop concepts and analyze data - Output from computer software and calculators is displayed throughout the textbook. The discussion focuses on interpretation of the output, rather than on the keystrokes needed to create the output.
- The widely-recognized and popular Minitab statistical software is used for most of the output examples, but we also include, as appropriate, sample output from SPSS, Excel and the TI-83+ graphing calculator.
- Technology manuals (featuring keystrokes) are available to accompany the published text. They are designed to work hand-in-glove with the book and feature worked examples and exercises using the appropriate technology.
Provides help to students exactly when they need it - Several different types of boxed items offer at-a-glance information to aid students in comprehending material in the main text. These include:
- IN WORDS: Offers an explanation of the complicated symbolic notation and formal definitions found in the text in a non-technical, less formal way to help the student understand “what it really means”.
- RECALL: When concepts are presented that rely on information learned in previous chapters, RECALL boxes direct students back to the section where the concept was first introduced.
- ON THE SHOULDERS OF…HISTORY AS DISCOVERY: Many chapters highlight a significant contribution to statistics and the people behind the discovery. “On the Shoulders of…” boxes give students a historical perspective, showing the context in which major statistical ideas were developed. What distinguishes this feature from traditional “history boxes” is that the focus is on the motivation for the discovery rather than a recitation of facts about a famous statistician.
Teach through the graphics – In recognition of the fact that many students are visual learners, Agresti and Franklin have thoroughly annotated the figures with labels to identify noteworthy aspects in each illustration that may not be obvious to the inexperienced student. Further, many figure captions include a question designed to challenge the student to actively interpret and think about the information being communicated by the graphic. The answers to the questions appear at the end of the chapter.
- The graphics also feature a pedagogical use of color to help students recognize patterns and to distinguish between statistics and parameters. This attention to detail and concern for presenting graphical information clearly set Agresti and Franklin apart from other books intended for this course.
Assessment is offered to evaluate and improve student learning
- the exercises play a vital role in assessing student comprehension.
- Powerpoint slides are available, with built in Personal Response Questions (clicker questions) to cater to the "just in time" learning philosophy. The Personal Response questions are concept oriented and can be used to assess how many/ which of the students have mastered a concept and are ready to move aon. These PPT questions are available to instructors from the Instructor Resource Center, for download, and also within MyMathLab.
- MyStatLab offers algorithmically generated exercises, that are objective based, to provide students with the practice they need to master concepts and techniques. MyStatLab also has a quizzing component to assess student learning.
Agresti/ Franklin: Statistics
TABLE OF CONTENTS
Note: each chapter concludes with Answers to Chapter Figure Questions; Chapter Summary; Summary of notation; Chapter Exercises.
1. Statistics: The Art and Science of Learning from Data
1.1 How Can You Investigate Using Data?
1.2 We Learn about Populations Using Samples
1.3 What Role do Computers Play in Statistics?
2. Exploring Data with Graphs and Numerical Summaries
2.1What Are the Types of Data?
2.2 How Can We Describe Data Using Graphical Summaries?
2.3 How Can We Describe the Center of Quantitative Data?
2.4 How Can We Describe the Spread of Quantitative Data?
2.5 How Can Measures of Position Describe Spread?
2.6 How Are Descriptive Summaries Misused?
3. Association: Contingency, Correlation, and Regression
3.1 How Can We Explore the Association between Two Categorical Variables?
3.2 How Can We Explore the Association between Two Quantitative Variables?
3.3 How Can We Predict the Outcome of a Variable
3.4 What are Some Cautions in Analyzing Associations?
4. Gathering Data
4.1 Should We Experiment or Should We Merely Observe?
4.2 What Are Good Ways and Poor Ways to Sample?
4.3 What Are Good Ways and Poor Ways to Experiment?
4.4 What Are Other Ways to Perform Experimental and Observational Studies?
5. Probability in our Daily Lives
5.1 How Can Probability Quantify Randomness?
5.2 How Can We Find Probabilities?
5.3 Conditional Probability: What’s the Probability of A, Given B?
5.4 Applying the Probability Rules
6. Probability Distributions
6.1 How Can We Summarize Possible Outcomes and their Probabilities?
6.2 How Can We Find Probabilities for Bell-Shaped Distributions?
6.3 How Can We Find Probabilities when Each Observation Has Two Possible
6.4 How Likely Are the Possible Values of a Statistic?: The Sampling Distribution
6.5 How Close Are Sample Means to Population Means
6.6 How Can We Make Inferences about a Population?
7. Statistical Inference: Confidence Intervals
7.1 What Are Point and Interval Estimates of Population Parameters?
7.2 How Can We Construct a Confidence Interval to Estimate a Population Proportion?
7.3 How Can We Construct a Confidence Interval to Estimate a Population Mean?
7.4 How Do We Choose the Sample Size for a Study
7.5 How Do Computers Make New Estimation Methods Possible?
8. Statistical Inference: Significance Tests about Hypotheses
8.1 What Are the Steps for Performing a Significance Test?
8.2 Significance Tests about Proportions
8.3 Significance Tests about Means
8.4 Decisions and Types of Errors in Significance Tests
8.5 Limitations of Significance Tests
8.6 How Likely Is Type II Error (Not Rejecting H0, Even though it’s False)?
9. Comparing Two Groups
9.1 Categorical Response: How Can We Compare Two Proportions?
9.2 Quantitative Response: How Can We Compare Two Means?
9.3 Other Ways of Comparing Means and Comparing Proportions
9.4 How Can We Analyze Dependent Samples?
9.5 How Can We Adjust for Effects of Other Variables?
10. Analyzing the Association Between Categorical Variables
10.1 What Is Independence and What Is Association?
10.2 How Can We Test whether Categorical Variables are Independent?
10.3 How Strong is the Association?
10.4 How Can Residuals Reveal the Pattern of Association?
10.5 What if the Sample Size is Small? Fisher’s Exact Test
11. Analyzing Association between Quantitative Variables: Regression Analysis
11.1 How Can We “Model” How Two Variables Are Related?
11.2 How Can We Describe Strength of Association?
11.3 How Can We Make Inferences about the Association?
11.4 What Do We Learn from How the Data Vary around the Regression Line?
11.5 Exponential Regression: A Model for Nonlinearity
12. Multiple Regression
12.1 How Can We Use Several Variables to Predict a Response?
12.2 Extending the Correlation and R-squared for Multiple Regression
12.3 How Can We Use Multiple Regression to Make Inferences?
12.4 Checking a Regression Model Using Residual Plots
12.5 How Can Regression Include Categorical Predictors?
12.6 How Can We Model a Categorical Response?
13. Comparing Groups: Analysis of Variance Methods
13.1 How Can We Compare Several Means?: One-Way ANOVA
13.2 How Should We Follow Up an ANOVA F test
13.3 What if there Are Two Factors?: Two-way ANOVA
14. Nonparametric Statistics
14.1 How Can We Compare Two Groups by Ranking?
14.2 Nonparametric Methods for Several Groups and for Matched Pairs
Appendices
Appendix A: Tables
Appendix B: Selected Answers
Index
Photo Credits
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Statistics: The Art and Science of Learning from Data, 2/E
Agresti & Franklin
©2009 | Prentice Hall | Cloth Bound w/CD-ROM; 848 pp | Instock
ISBN-10: 0135131995 | ISBN-13: 9780135131992
Brief Description | Buy from myPearsonStore
REVIEWER and CLASS TEST COMMENTS:
"This was one of the most enjoyable texts that I have come across. I learned a lot from this book and it has made statistics a lot more fun to teach." - Nazanin Azarnia [CLASS TESTER], Sante Fe Community College, FL
"Good descriptions of concepts, does help them with procedures, strives to help students learn to solve problems...a book my students seemed to find readable." - Ginger Rowell [CLASS TESTER], Middle Tennessee University
"Overall, my experience with this text was very positive. The inference chapters were especially strong....Many topics were presented in a novel way compared to other texts. Examples and homework problems were the most relevant and interesting that I have ever seen." - John Seppala [CLASS TESTER], Valdosta State University, GA
“The examples are one of the strong points of this text…” — Martin Lindquist, Columbia University
“The examples used in this text are excellent. … A student…is likely to believe that statistics is actually useful, and know how to use it, and also how not to use it.” — Alla Sikorskii, Michigan State University
“I think the writing style in these chapters is better than my current text…” — Robert Price, East Tennessee State University
“Keep students’ needs in mind and reduce confusion; This is an important distinguishing characteristic…” — Rob Paige, Texas Tech
“Agresti/Franklin’s use of current and interesting topics is very impressive…” — Dawn White, CSU Bakersfield
“The examples in the text are outstanding. Coincidences, therapeutic touch, astrology, basketball, election results, medical trials, etc. – lots of interesting and relevant examples. I really enjoyed reading the text and I’m sure that my students would also.” – Martin Jones, College of Charleston
“The quality of the Agresti/Franklin examples would strongly influence my decision to adopt this book! I found these examples to be clearly explained, timely, and from a broad range of topics…” – Leslie Hayes, St. Joseph’s University
“Statistics is just as much a problem-solving technique as it is a mathematical science. Students need to see the importance of statistics in everyday life and scientific research. They need to learn how to become educated citizens as well as possible future researchers…From what I have seen…the text seems to do an excellent job promoting this. The chapters are filled with interesting examples…Furthermore, there are more than enough exercises.” – Stephanie Pickle, Virginia Polytechnic Institute and State University
STUDENT QUOTES (CLASS TESTERS)
“ I thought examples were interesting and they helped my understanding.”
Glen Pauch, University of Manitoba
“…the interesting examples…peaked my interest in the material.”
“enjoyed the examples…modern situations with very up-to-date information. I also found that they illustrated the concepts well.”
Benjamin Meek, University of Manitoba
"It definitely showed me how important statistics is in real world applications. It encouraged me to think about how in my career, statistics would be helpful."
Jenna Howells, University of Manitoba
“…real life examples were used to make the information relative and useful which made me think more about what I was learning.”
Brenda Klassen, University of Manitoba
“…everyday examples that were relevant in our lives so it made me think about how statistics is used all the time.”
Valene Bertrand, University of Manitoba
“…[the examples] are really good at illustrating concepts.”
Sarah Voss, College of Charleston
“..I enjoyed the true to life examples…seeing such examples allowed me to relate statistics to real life…”
Shannon Sheehan, College of Charleston
“I found the examples to do a great job explaining and illustrating the topics discussed.”
Troy Wood, University of Georgia
“The examples were excellent, interesting and easy to relate to..”
Lindsey Kenoe, University of Georgia
“..examples dealt with current events and issues of interest to all the students using this book.”
Benjamin Cobb, UGA
“…what an awesome job of explaining concepts through examples and exercises!”
Dinean Stevens, UGA
“I really don’t want this to sound corny or exaggerated…but this is really the first math class I’ve enjoyed and I think it’s not just because of the nature of statistics but because of the examples and scenarios used.”
David Mahon, UGA
“…these examples are actually about real life: teen drinking, politics, internet use…other books have examples that are completely unrealistic…”
Logan Troutman, Valdosta State University
“I loved the exercise sets because they were clear & understandable…”
Jaclyn Planas, Central Connecticut State University
[Examples]….very relevant, current. They made statistics come to life, instead of just being about numbers”
Michael C. Larkins, Middle TN State U
"I’ve often struggled in math and need very clear explanations. This book gave step-by-step examples that made it easy to understand."
Amanda M. Jenkins, Middle TN State U
"I would say that I highly recommend this book. Its easy to read, instead of giving several formulas, the book preps you on how to read the passage and understand what the passage asks you to do. …not only did the book give the answer (which is what all books do), but the book described the answer so that you knew why that was the answer. "
Katie, Sante Fe CC
Alan Agresti is Distinguished Professor in the Department of Statistics at the University of Florida. He has been teaching statistics there for 30 years, including the development of three courses in statistical methods for social science students and three courses in categorical data analysis. He is author of over 100 refereed article and four texts including "Statistical Methods for the Social Sciences" (with Barbara Finlay, Prentice Hall, 3rd edition 1997) and "Categorical Data Analysis" (Wiley, 2nd edition 2002). He is a Fellow of the American Statistical Association and recipient of an Honorary Doctor of Science from De Montfort University in the UK. In 2003 he was named "Statistician of the Year" by the Chicago chapter of the American Statistical Association and in 2004 he was the first honoree of the Herman Callaert Leadership Award in Biostatistical Education and Dissemination awarded by the University of Limburgs, Belgium. He has held visiting positions at Harvard University, Boston University, London School of Economics, and Imperial College and has taught courses or short courses for universities and companies in about 20 countries worldwide. He has also received teaching awards from UF and an excellence in writing award from John Wiley & Sons.
Christine Franklin is a Lecturer and Honors Professor in the Department of Statistics at the University of Georgia. She is beginning her 16th year at UGA, her 25th year as college faculty in statistics. Chris has been actively involved at the national level with promoting statistical education at the K-12 level and college undergraduate level since the 1980's. Her involvement with the AP Statistics program includes preparing teachers to teach AP Statistics and serving as a table leader at the AP Statistics readings since 1997. She also conducts College Board workshops and in 1998, began teaching a new course at UGA that she designed for secondary math teachers. Her most recent course development has been a new master's level course in probability and statistics for K-8 teachers. Much of the development of these courses was based on her involvement serving as a statistical advisor for the 2000 NCTM Principles and Standards of Mathematics. She is also the undergraduate coordinator in the Statistics department at UGA and is presently working to restructure the undergraduate statistics major.
Chris has found her most challenging educational role to be serving as Chairperson of her local school district's Board of Education. This has also been a very rewarding experience, especially working with teachers in her system and with the curriculum and instruction.
Most important for Chris is her family. Her husband, Dale Green, is a physician. They have two boys, Corey (a junior in high school and taking AP Statistics this year) and Cody (a fourth grader). Her most recent memorable experience was backpacking for 11 days in Philmont, NM with her older son and the boy scouts.
STUDENT EDITION BCC:
Why buy this book?
Listen to what students who have used this text have to say!
“I really don’t want this to sound corny…but this is the first math class I’ve enjoyed and I think it’s not just because of the nature of statistics but because of the examples and scenarios [in the text].” David Mahon, University of Georgia
“…the examples are actually about real life: teen drinking, politics, internet use…other books have examples that are completely unrealistic…”Logan Troutman, ValdostaStateUniversity
“I’ve often struggled in math and need very clear explanations. This book gave step-by-step examples that made it easy to understand.” Amanda M. Jenkins, MiddleTennesseeStateUniversity
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The Student Study Pack provides comprehensive materials designed to enhance your study experience! It includes: · Student Solutions Manual · CD-lecture videos (Instructor working out each text example) · Technology Manual (Excel, MINITAB, TI, and SPSS) · Access to Pearson Tutor Center.
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