|
|
Introduction to Stadistics and Data Analysis
Peck, Roxy
|
Últimas novedades
estadística
|
|
Roxy Peck, Chris Olsen and Jay Devore’s new edition uses real data and attention-grabbing examples to introduce students to the study of statistics and data analysis. The Third Edition includes coverage of the graphing calculator and includes expanded coverage of probability. Traditional in structure yet modern in approach, this text guides students through an intuition-based learning process that stresses interpretation and communication of statistical information. It helps students grasp concepts and cement their comprehension by using simple notation-frequently substituting words for symbols. Hands-on activities and interactive applets allow students to practice statistics firsthand.
Features
"Communicating and Interpreting the Results of Statistical Analysis" sections emphasize the importance of being able to interpret statistical output and communicate its meaning to non-statisticians.
Real data gives students authentic scenarios that help them understand statistical concepts in a realistic context.
Fresh and interesting examples and exercises involving real data extracted from current journal articles, newspapers, and other published sources are included in the text.
The book features broad coverage of sampling, survey design and experimental design coverage of transformations and nonlinear regression; and an emphasis on graphical display as a necessary component of data analysis.
The book highlights the role of the computer in contemporary statistics through numerous printouts and exercises that can be solved by computer.
Several Java applets, used in conjunction with activities that appear at the end of the chapter, provide visual insight into statistical concepts.
CengageNOW’’s Personalized Study plans allow students to study smarter by diagnosing their weak areas, and focusing their attention on what they need to learn. Based on responses to chapter pre-tests, the plans direct students to multimedia and interactive exercises that help them better learn the material. A post-test measures their understanding.
Transparencies and Microsoft® PowerPoint® Slides in the Instructor’’s Resource Binder make lecture and class preparation quick and easy.
1. THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS.
Three Reasons to Study Statistics. The Nature and Role of Variability. Statistics and the Data Analysis Process. Types of Data and Some Simple Graphical Displays. Activity 1.1: Head Sizes: Understanding Variability. Activity 1.2: Estimating Sizes. Activity 1.3: A Meaningful Paragraph.
2. COLLECTING DATA SENSIBLY.
Statistical Studies: Observation and Experimentation. Sampling. Simple Comparative Experiments. More on Experimental Design. More on Observational Studies: Designing Surveys (optional). Communicating and Interpreting the Results of Statistical Analyses. Activity 2.1: Designing a Sampling Plan. Activity 2.2: An Experiment to Test for the Stroop Effect. Activity 2.3: McDonalds and the Next 100 Billion Burgers. Activity 2.4: Video Games and Pain Management. Graphing Calculator Explorations.
3. GRAPHICAL METHODS FOR DESCRIBING DATA.
Displaying Categorical Data: Comparative Bar Charts and Pie Charts. Displaying Numerical Data: Stem-and-Leaf Displays. Displaying Numerical Data: Frequency Distributions and Histograms. Displaying Bivariate Numerical Data. Communicating and Interpreting the Results of Statistical Analyses. Activity 3.1: Locating States. Activity 3.2: Bean Counters! Graphing Calculator Explorations.
4. NUMERICAL METHODS FOR DESCRIBING DATA.
Describing the Center of a Data Set. Describing Variability in a Data Set. Summarizing a Data Set: Boxplots. Interpreting Center and Variability: Chebyshev’’s Rule, the Empirical Rule, and z Scores. Communicating and Interpreting the Results of Statistical Analyses. Activity 4.1: Collecting and Summarizing Numerical Data. Activity 4.2: Airline Passenger Weights. Activity 4.3: Boxplot Shapes. Graphing Calculator Explorations.
5. SUMMARIZING BIVARIATE DATA.
Correlation. Linear Regression: fitting a Line to Bivariate Data. Assessing the Fit of a Line. Nonlinear Relationships and Transformations. Logistic Regression (Optional). Communicating and Interpreting the Results of Statistical Analyses. Activity 5.1: Exploring Correlation and Regression Technology Activity (Applets). Activity 5.2: Age and Flexibility. Graphing calculator Explorations.
6. PROBABILITY.
Chance Experiments and Events. Definition of Probability. Basic Properties of Probability. Conditional Probability. Independence. Some General Probability Rules. Estimating Probabilities Empirically and Using Simulation. Activity 6.1: Kisses. Activity 6.2: A Crisis for European Sports Fans? Activity 6.3: The "Hot Hand" in Basketball. Graphing Calculator Explorations.
7. RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS.
Random Variables. Probability Distributions for Discrete Random Variables. Probability Distributions for continuous Random Variables. Mean and Standard Deviation of a Random Variable. The Binomial and Geometric Distributions. Normal Distributions. Checking for Normality and Normalizing Transformations. Using the Normal Distribution to Approximate a Discrete Distribution. Activity 7.1: Rotten Eggs. Graphing Calculator Explorations.
8. SAMPLING VARIABILITY AND SAMPLING DISTRIBUTIONS.
Statistics and Sampling Variability. The Sampling Distribution of a Sample Mean. The Sampling distribution of a Sample Proportion. Activity 8.1: Do Students Who Take the SAT Multiple Times Have an Advantage in College Admissions? Graphing Calculator Explorations.
9. ESTIMATION USING A SINGLE SAMPLE.
Point Estimates. Large-Sample Confidence Interval for a Population Proportion. Confidence Interval for a Population Mean. Communicating and Interpreting the Results of Statistical Analyses. Activity 9.1: Getting a Feel for Confidence Level. Activity 9.2: An Alternative Confidence Interval for a Population Proportion. Graphing Calculator Explorations.
10. HYPOTHESIS TESTING USING A SINGLE SAMPLE.
Hypotheses and Test Procedures. Errors in Hypothesis Testing. Large-Sample Hypothesis Tests for a Population Proportion. Hypothesis Tests for a Population Mean. Power and the Probability of Type II Error. Communicating and Interpreting the Results of Statistical Analyses. Activity 10.1: Comparing the t and z Distributions. Graphing Calculator Explorations.
11. COMPARING TWO POPULATIONS OR TREATMENTS.
Inferences Concerning the Difference Between Two Population or Treatment Means using Independent Samples. Inferences Concerning the Difference Between Two Population or Treatment Means using Paired Samples. Large-Sample Inferences Concerning a Difference Between Two Population or Treatment Proportions. Communicating and Interpreting the Results of Statistical Analyses. Activity 11.1: Helium-Filled Footballs? Activity 11.2: Thinking About Data Collection. Graphing Calculator Explorations.
12. THE ANALYSIS OF CATEGORICAL DATA AND GOODNESS-OF-FIT TESTS.
Chi-Square Tests for Univariate Categorical Data. Tests for Homogeneity and Independence in a Two-Way Table. Communicating and Interpreting the Results of Statistical Analyses. Activity 12.1: Pick a Number, Any Number. Activity 12.2: Color and Perceived Taste. Graphing Calculator Explorations.
13. SIMPLE LINEAR REGRESSION AND CORRELATION: INFERENTIAL METHODS.
The Simple Linear Regression Model. Inferences About the Slope of the Population Regression Line. Checking Model Adequacy. Inferences Based on the Estimated Regression Line (Optional). Inferences About the Population Correlation Coefficient (Optional). Communicating and Interpreting the Results of Statistical Analyses. Activity 13.1: Are Tall Women from "Big" Families? Graphing Calculator Explorations.
14. MULTIPLE REGRESSION ANALYSIS.
Multiple Regression Models. Fitting a Model and Assessing Its Utility. Inferences Based on an Estimated Model (Online). Variable Selection and Other Issues in Multiple Regression (Online). Communicating and Interpreting the Results of Statistical Analyses (Online). Activity 14.1: Exploring the Relationship Between Number of Predictors and Sample Size.
15. ANALYSIS OF VARIANCE.
Single-Factor ANOVA and the F Test. Multiple Comparisons. The F Test for a Randomized Block Experiment (Online). Two-Factor ANOVA (Online). Communicating and Interpreting the Results of Statistical Analysis (Online). Activity 15.1: Exploring Single-Factor ANOVA. Appendix: ANOVA computations (Online). Graphing Calculator Exploration.
16. NONPARAMETRIC STATISTICAL METHODS (ONLINE).
Distribution-Free Procedures for Inferences about a Difference Between Two Population or Treatment Means Using Independent Samples (Online). Distribution-Free Procedures for Inferences Concerning a Difference. Between Two Population Means Using Paired Samples (Online). Distribution-Free ANOVA (Online).
Appendix: Statistical Tables.
Answers to Selected odd-Numbered Exercises.
Index.
Enhanced WebAssign is the most widely used homework system in higher education. Available with the third edition of Peck/Olsen/Devore’’s INTRODUCTION TO STATISTICS AND DATA ANALYSIS, Enhanced WebAssign allows you to assign, collect, grade, and record homework assignments via the web. This proven homework system has been enhanced to include links to the textbook sections, video examples, problem specific tutorials. Enhanced WebAssign is more than a homework system; it is a complete learning system for students in the introductory statistics course.Interesting new examples and exercises with real data-Nearly 100 new examples and hundreds of new or updated exercises with current data from journals, newspapers, and other published sources, helping students understand statistical concepts in a realistic, relevant context. There are now over 1,100 exercises in the third edition.Eight new activities bring the total to 33. Found at the ends of chapters, these hands-on activities allow students to see statistics unfold before their eyes as they conduct their own experiments. [I] New optional material on logistic regression in Chapter 5, "Summarizing Bivariate Data," assures complete coverage of this important topic.New optional material on logistic regression in Chapter 5, "Summarizing Bivariate Data," assures complete coverage of this important topic.A new chapter on Nonparametric Methods is available online, providing you with the option of covering this topic if you wish.
{Supplements}
{Quotes}
Roxy Peck
Roxy Peck is Associate Dean of the College of Science and Mathematics and Professor of Statistics at California Polytechnic State University, San Luis Obispo. Roxy has been on the faculty at Cal Poly since 1979, serving for six years as Chair of the Statistics Department prior to becoming Associate Dean. She received an M.S. in Mathematics and a Ph.D. in Applied Statistics from the University of California, Riverside. Dr. Peck is nationally known in the area of statistics education, and in 2003 she received the American Statistical Association’s Founder’s Award, recognizing her contributions to K-12 and undergraduate statistics education. She is a Fellow of the American Statistical Association and an elected member of the International Statistics Institute. Dr. Peck has recently completed five years as the Chief Reader for the AP Statistics Exam, and currently chairs the American Statistical Association’s Joint Committee with the National Council of Teachers of Mathematics on Curriculum in Statistics and Probability for Grades K-12. In addition to being co-editor of STATISTICAL CASE STUDIES: A COLLABORATION BETWEEN ACADEME AND INDUSTRY, Dr. Peck is the co-author of STATISTICS: THE EXPLORATION AND ANALYSIS OF DATA, Fifth Edition and INTRODUCTION TO STATISTICS AND DATA ANALYSIS, Second Edition. Outside the classroom and the office, Dr. Peck likes to travel and spends her spare time reading mystery novels. She also collects Navajo rugs, and heads to New Mexico whenever she can find the time.
Chris Olsen
Chris Olsen has taught statistics at George Washington High School in Cedar Rapids, IA, for over 25 years. Chris is a past member of the AP Statistics Test Development Committee and the author of the Teacher’s Guide for Advanced Placement Statistics. He has been a table leader at the AP Statistics reading for 6 years, and since the summer of 1996 has been a consultant to the College Board. Chris leads workshops and institutes for AP Statistics teachers in the United States and internationally. Chris was the Iowa recipient of the Presidential Award for Excellence in Science and Mathematics Teaching in 1986. He was a regional winner of the IBM Computer Teacher of the Year award in 1988, and received the Siemens Award for Advanced Placement in mathematics in 1999. Chris is a frequent contributor to the AP Statistics listserv, and has reviewed materials for "The Mathematics Teacher," the AP Central Web site, The "American Statistician," and the "Journal of the American Statistical Association." He currently writes a column for "Stats" magazine. Chris graduated from Iowa State University with a major in mathematics, and while acquiring graduate degrees at the University of Iowa concentrated on statistics, computer programming, psychometrics, and test development. Currently he divides his duties between teaching and evaluation; in addition to teaching he is the assessment facilitator for the Cedar Rapids, Iowa, Community Schools. In his spare time he enjoys reading and hiking. He and his wife have a daughter, Anna, who is a graduate student in Civil Engineering at Cal Tech.
Jay L. Devore
JAY DEVORE received a B.S. in Engineering Science from UC Berkeley and a Ph.D. in Statistics from Stanford University. He previously taught at the University of Florida and Oberlin College, and has had visiting positions at Stanford, Harvard, the University of Washington, and New York University. He has been at California Polytechnic State University, San Luis Obispo since 1977, where he is currently Professor and Chair of the Department of Statistics. He is a Fellow of the American Statistical Association, an Associate Editor for the Journal of the American Statistical Association, and received the Distinguished Teaching Award from Cal Poly in 1991. His recreational interests include reading, playing tennis, traveling, and cooking and eating good food.
HomeInstructors
New TitlesGeneral Chemistry TextbookPhysics for the Life Sciences TextbookOrder Inspection CopiesOnline ResourcesRep locatorStudents
Online Student ResourcesBookshopsAuthors
Review processProposal guidelinesUnited KingdomChange your regionSearch Go
AccountingBusiness & TechnologyBusiness CommunicationBusiness EducationBusiness LawBusiness MathematicsBusiness StatisticsCareer Investigation & ReadinessCertificationCommunicationsComputer ApplicationsComputer EducationDecision SciencesEconomicsFinanceIntroduction to BusinessManagementMarketingOffice TechnologyReal EstateReferenceTaxationTechnologyAnthropologyArtCommunication and MediaCounselling/PsychotherapyCriminal JusticeDevelopmental EnglishEnglishEnglish as a Second LanguageFrenchGermanHistoryHuman ServicesItalianModern LanguageMusicPhilosophyPolitical SciencePsychologyReligionSocial WorkSociologySpanishAstronomyChemistryEarth ScienceEngineeringHealthLife SciencesMathematicsNutritionOceanographyPhysicsAssessment, Training, and ProjectsComputer ConceptsComputer ScienceDatabasesGame Design & DevelopmentGraphic CommunicationsHelp Desk/Desktop SupportInternetMedia Arts & DesignMISMusic TechnologyNetworking & SecurityOffice SuitesOperating SystemsPC Repair/A+Presentation ToolsProgrammingProject ManagementSoft SkillsSpreadsheetsWeb Design & DevelopmentWord ProcessingAgriscienceAutomotive and MechanicsAviationCatering and HospitalityCollege SuccessEducationElectronics and EngineeringHair & BeautyLeisure and ToursimNursing, Medical and DentistryPhotography, Multimedia and DesignProfessional Development and Study SkillsTradesCengage Learning EMEAEnglish Language TeachingGlobalHigher EducationLibrary & ReferenceAbout UsCopyright, Terms & ConditionsPrivacy PolicyContact UsCareersWebsite Design by Mulberry Interactive Ltd |
| indíce |
. THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS.
Three Reasons to Study Statistics. The Nature and Role of Variability. Statistics and the Data Analysis Process. Types of Data and Some Simple Graphical Displays. Activity 1.1: Head Sizes: Understanding Variability. Activity 1.2: Estimating Sizes. Activity 1.3: A Meaningful Paragraph.
2. COLLECTING DATA SENSIBLY.
Statistical Studies: Observation and Experimentation. Sampling. Simple Comparative Experiments. More on Experimental Design. More on Observational Studies: Designing Surveys (optional). Communicating and Interpreting the Results of Statistical Analyses. Activity 2.1: Designing a Sampling Plan. Activity 2.2: An Experiment to Test for the Stroop Effect. Activity 2.3: McDonalds and the Next 100 Billion Burgers. Activity 2.4: Video Games and Pain Management. Graphing Calculator Explorations.
3. GRAPHICAL METHODS FOR DESCRIBING DATA.
Displaying Categorical Data: Comparative Bar Charts and Pie Charts. Displaying Numerical Data: Stem-and-Leaf Displays. Displaying Numerical Data: Frequency Distributions and Histograms. Displaying Bivariate Numerical Data. Communicating and Interpreting the Results of Statistical Analyses. Activity 3.1: Locating States. Activity 3.2: Bean Counters! Graphing Calculator Explorations.
4. NUMERICAL METHODS FOR DESCRIBING DATA.
Describing the Center of a Data Set. Describing Variability in a Data Set. Summarizing a Data Set: Boxplots. Interpreting Center and Variability: Chebyshev’’s Rule, the Empirical Rule, and z Scores. Communicating and Interpreting the Results of Statistical Analyses. Activity 4.1: Collecting and Summarizing Numerical Data. Activity 4.2: Airline Passenger Weights. Activity 4.3: Boxplot Shapes. Graphing Calculator Explorations.
5. SUMMARIZING BIVARIATE DATA.
Correlation. Linear Regression: fitting a Line to Bivariate Data. Assessing the Fit of a Line. Nonlinear Relationships and Transformations. Logistic Regression (Optional). Communicating and Interpreting the Results of Statistical Analyses. Activity 5.1: Exploring Correlation and Regression Technology Activity (Applets). Activity 5.2: Age and Flexibility. Graphing calculator Explorations.
6. PROBABILITY.
Chance Experiments and Events. Definition of Probability. Basic Properties of Probability. Conditional Probability. Independence. Some General Probability Rules. Estimating Probabilities Empirically and Using Simulation. Activity 6.1: Kisses. Activity 6.2: A Crisis for European Sports Fans? Activity 6.3: The "Hot Hand" in Basketball. Graphing Calculator Explorations.
7. RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS.
Random Variables. Probability Distributions for Discrete Random Variables. Probability Distributions for continuous Random Variables. Mean and Standard Deviation of a Random Variable. The Binomial and Geometric Distributions. Normal Distributions. Checking for Normality and Normalizing Transformations. Using the Normal Distribution to Approximate a Discrete Distribution. Activity 7.1: Rotten Eggs. Graphing Calculator Explorations.
8. SAMPLING VARIABILITY AND SAMPLING DISTRIBUTIONS.
Statistics and Sampling Variability. The Sampling Distribution of a Sample Mean. The Sampling distribution of a Sample Proportion. Activity 8.1: Do Students Who Take the SAT Multiple Times Have an Advantage in College Admissions? Graphing Calculator Explorations.
9. ESTIMATION USING A SINGLE SAMPLE.
Point Estimates. Large-Sample Confidence Interval for a Population Proportion. Confidence Interval for a Population Mean. Communicating and Interpreting the Results of Statistical Analyses. Activity 9.1: Getting a Feel for Confidence Level. Activity 9.2: An Alternative Confidence Interval for a Population Proportion. Graphing Calculator Explorations.
10. HYPOTHESIS TESTING USING A SINGLE SAMPLE.
Hypotheses and Test Procedures. Errors in Hypothesis Testing. Large-Sample Hypothesis Tests for a Population Proportion. Hypothesis Tests for a Population Mean. Power and the Probability of Type II Error. Communicating and Interpreting the Results of Statistical Analyses. Activity 10.1: Comparing the t and z Distributions. Graphing Calculator Explorations.
11. COMPARING TWO POPULATIONS OR TREATMENTS.
Inferences Concerning the Difference Between Two Population or Treatment Means using Independent Samples. Inferences Concerning the Difference Between Two Population or Treatment Means using Paired Samples. Large-Sample Inferences Concerning a Difference Between Two Population or Treatment Proportions. Communicating and Interpreting the Results of Statistical Analyses. Activity 11.1: Helium-Filled Footballs? Activity 11.2: Thinking About Data Collection. Graphing Calculator Explorations.
12. THE ANALYSIS OF CATEGORICAL DATA AND GOODNESS-OF-FIT TESTS.
Chi-Square Tests for Univariate Categorical Data. Tests for Homogeneity and Independence in a Two-Way Table. Communicating and Interpreting the Results of Statistical Analyses. Activity 12.1: Pick a Number, Any Number. Activity 12.2: Color and Perceived Taste. Graphing Calculator Explorations.
13. SIMPLE LINEAR REGRESSION AND CORRELATION: INFERENTIAL METHODS.
The Simple Linear Regression Model. Inferences About the Slope of the Population Regression Line. Checking Model Adequacy. Inferences Based on the Estimated Regression Line (Optional). Inferences About the Population Correlation Coefficient (Optional). Communicating and Interpreting the Results of Statistical Analyses. Activity 13.1: Are Tall Women from "Big" Families? Graphing Calculator Explorations.
14. MULTIPLE REGRESSION ANALYSIS.
Multiple Regression Models. Fitting a Model and Assessing Its Utility. Inferences Based on an Estimated Model (Online). Variable Selection and Other Issues in Multiple Regression (Online). Communicating and Interpreting the Results of Statistical Analyses (Online). Activity 14.1: Exploring the Relationship Between Number of Predictors and Sample Size.
15. ANALYSIS OF VARIANCE.
Single-Factor ANOVA and the F Test. Multiple Comparisons. The F Test for a Randomized Block Experiment (Online). Two-Factor ANOVA (Online). Communicating and Interpreting the Results of Statistical Analysis (Online). Activity 15.1: Exploring Single-Factor ANOVA. Appendix: ANOVA computations (Online). Graphing Calculator Exploration.
16. NONPARAMETRIC STATISTICAL METHODS (ONLINE).
Distribution-Free Procedures for Inferences about a Difference Between Two Population or Treatment Means Using Independent Samples (Online). Distribution-Free Procedures for Inferences Concerning a Difference. Between Two Population Means Using Paired Samples (Online). Distribution-Free ANOVA (Online).
Appendix: Statistical Tables.
Answers to Selected odd-Numbered Exercises.
Index.
Enhanced WebAssign is the most widely used homework system in higher education. Available with the third edition of Peck/Olsen/Devore’’s INTRODUCTION TO STATISTICS AND DATA ANALYSIS, Enhanced WebAssign allows you to assign, collect, grade, and record homework assignments via the web. This proven homework system has been enhanced to include links to the textbook sections, video examples, problem specific tutorials. Enhanced WebAssign is more than a homework system; it is a complete learning system for students in the introductory statistics course.Interesting new examples and exercises with real data-Nearly 100 new examples and hundreds of new or updated exercises with current data from journals, newspapers, and other published sources, helping students understand statistical concepts in a realistic, relevant context. There are now over 1,100 exercises in the third edition.Eight new activities bring the total to 33. Found at the ends of chapters, these hands-on activities allow students to see statistics unfold before their eyes as they conduct their own experiments. [I] New optional material on logistic regression in Chapter 5, "Summarizing Bivariate Data," assures complete coverage of this important topic.New optional material on logistic regression in Chapter 5, "Summarizing Bivariate Data," assures complete coverage of this important topic.A new chapter on Nonparametric Methods is available online, providing you with the option of covering this topic if you wish.
{Supplements}
{Quotes}
Roxy Peck
Roxy Peck is Associate Dean of the College of Science and Mathematics and Professor of Statistics at California Polytechnic State University, San Luis Obispo. Roxy has been on the faculty at Cal Poly since 1979, serving for six years as Chair of the Statistics Department prior to becoming Associate Dean. She received an M.S. in Mathematics and a Ph.D. in Applied Statistics from the University of California, Riverside. Dr. Peck is nationally known in the area of statistics education, and in 2003 she received the American Statistical Association’s Founder’s Award, recognizing her contributions to K-12 and undergraduate statistics education. She is a Fellow of the American Statistical Association and an elected member of the International Statistics Institute. Dr. Peck has recently completed five years as the Chief Reader for the AP Statistics Exam, and currently chairs the American Statistical Association’s Joint Committee with the National Council of Teachers of Mathematics on Curriculum in Statistics and Probability for Grades K-12. In addition to being co-editor of STATISTICAL CASE STUDIES: A COLLABORATION BETWEEN ACADEME AND INDUSTRY, Dr. Peck is the co-author of STATISTICS: THE EXPLORATION AND ANALYSIS OF DATA, Fifth Edition and INTRODUCTION TO STATISTICS AND DATA ANALYSIS, Second Edition. Outside the classroom and the office, Dr. Peck likes to travel and spends her spare time reading mystery novels. She also collects Navajo rugs, and heads to New Mexico whenever she can find the time.
Chris Olsen
Chris Olsen has taught statistics at George Washington High School in Cedar Rapids, IA, for over 25 years. Chris is a past member of the AP Statistics Test Development Committee and the author of the Teacher’s Guide for Advanced Placement Statistics. He has been a table leader at the AP Statistics reading for 6 years, and since the summer of 1996 has been a consultant to the College Board. Chris leads workshops and institutes for AP Statistics teachers in the United States and internationally. Chris was the Iowa recipient of the Presidential Award for Excellence in Science and Mathematics Teaching in 1986. He was a regional winner of the IBM Computer Teacher of the Year award in 1988, and received the Siemens Award for Advanced Placement in mathematics in 1999. Chris is a frequent contributor to the AP Statistics listserv, and has reviewed materials for "The Mathematics Teacher," the AP Central Web site, The "American Statistician," and the "Journal of the American Statistical Association." He currently writes a column for "Stats" magazine. Chris graduated from Iowa State University with a major in mathematics, and while acquiring graduate degrees at the University of Iowa concentrated on statistics, computer programming, psychometrics, and test development. Currently he divides his duties between teaching and evaluation; in addition to teaching he is the assessment facilitator for the Cedar Rapids, Iowa, Community Schools. In his spare time he enjoys reading and hiking. He and his wife have a daughter, Anna, who is a graduate student in Civil Engineering at Cal Tech.
Jay L. Devore
JAY DEVORE received a B.S. in Engineering Science from UC Berkeley and a Ph.D. in Statistics from Stanford University. He previously taught at the University of Florida and Oberlin College, and has had visiting positions at Stanford, Harvard, the University of Washington, and New York University. He has been at California Polytechnic State University, San Luis Obispo since 1977, where he is currently Professor and Chair of the Department of Statistics. He is a Fellow of the American Statistical Association, an Associate Editor for the Journal of the American Statistical Association, and received the Distinguished Teaching Award from Cal Poly in 1991. His recreational interests include reading, playing tennis, traveling, and cooking and eating good food.
HomeInstructors
New TitlesGeneral Chemistry TextbookPhysics for the Life Sciences TextbookOrder Inspection CopiesOnline ResourcesRep locatorStudents
Online Student ResourcesBookshopsAuthors
Review processProposal guidelinesUnited KingdomChange your regionSearch Go
AccountingBusiness & TechnologyBusiness CommunicationBusiness EducationBusiness LawBusiness MathematicsBusiness StatisticsCareer Investigation & ReadinessCertificationCommunicationsComputer ApplicationsComputer EducationDecision SciencesEconomicsFinanceIntroduction to BusinessManagementMarketingOffice TechnologyReal EstateReferenceTaxationTechnologyAnthropologyArtCommunication and MediaCounselling/PsychotherapyCriminal JusticeDevelopmental EnglishEnglishEnglish as a Second LanguageFrenchGermanHistoryHuman ServicesItalianModern LanguageMusicPhilosophyPolitical SciencePsychologyReligionSocial WorkSociologySpanishAstronomyChemistryEarth ScienceEngineeringHealthLife SciencesMathematicsNutritionOceanographyPhysicsAssessment, Training, and ProjectsComputer ConceptsComputer ScienceDatabasesGame Design & DevelopmentGraphic CommunicationsHelp Desk/Desktop SupportInternetMedia Arts & DesignMISMusic TechnologyNetworking & SecurityOffice SuitesOperating SystemsPC Repair/A+Presentation ToolsProgrammingProject ManagementSoft SkillsSpreadsheetsWeb Design & DevelopmentWord ProcessingAgriscienceAutomotive and MechanicsAviationCatering and HospitalityCollege SuccessEducationElectronics and EngineeringHair & BeautyLeisure and ToursimNursing, Medical and DentistryPhotography, Multimedia and DesignProfessional Development and Study SkillsTradesCengage Learning EMEAEnglish Language TeachingGlobalHigher EducationLibrary & ReferenceAbout UsCopyright, Terms & ConditionsPrivacy PolicyContact UsCareersWebsite Design by Mulberry Interactive Ltd |
|
|