Statistics: The Exploration and Analysis of Data (with CD-ROM, InfoTrac, and Internet Companion) / Edition 5

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Overview


Jay Devore and Roxy Peck's attractive new text focuses on data analysis, citing real data in nearly all the examples, as the prime motivation for the study of statistics. Traditional in structure yet modern in approach, this text guides students through an intuition-based learning process that stresses the interpretation and communication of statistical output. Conceptual comprehension is cemented by the simplicity of notation-frequently substituting words for symbols. Hands-on activities and "Seeing Statistics" applets in each chapter allow students to practice statistics firsthand.
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Product Details

  • ISBN-13: 9780534467234
  • Publisher: Cengage Learning
  • Publication date: 3/1/2004
  • Edition description: Older Edition
  • Edition number: 5
  • Pages: 784
  • Product dimensions: 8.10 (w) x 10.10 (h) x 1.20 (d)

Meet the Author


Jay Devore earned his undergraduate degree in Engineering Science from the University of California at Berkeley, spent a year at the University of Sheffield in England, and finished his Ph.D. in statistics at Stanford University. He previously taught at the University of Florida and at Oberlin College and has had visiting appointments at Stanford, Harvard, the University of Washington, New York University, and Columbia University. From 1998 to 2006, Jay served as Chair of the Statistics Department at California Polytechnic State University, San Luis Obispo, which has an international reputation for activities in statistics education. In addition to this book, Jay has written several widely used engineering statistics texts and a book in applied mathematical statistics. He is currently collaborating on a business statistics text, and also serves as an Associate Editor for Reviews for several statistics journals. He is the recipient of a distinguished teaching award from Cal Poly and is a Fellow of the American Statistical Association. In his spare time, he enjoys reading, cooking and eating good food, tennis, and travel to faraway places. He is especially proud of his wife, Carol, a retired elementary school teacher, his daughter Allison, the executive director of a nonprofit organization in New York City, and his daughter Teresa, an ESL teacher in New York City.

Dr. Roxy Peck has been a professor in the Department of Statistics at California Polytechnic State University at San Luis Obispo since 1979, serving for six years as Chair and currently in her fourth year as Associate Dean of the College of Science and Mathematics. Dr. Peck has been very active in the field of statistics education. She is the co-author, with Dr. Jay Devore, of the fourth edition of STATISTICS: THE EXPLORATION AND ANALYSIS OF DATA, a widely used and highly regarded textbook for introductory statistics. She is also co-author of INTRODUCTION TO STATISTICS AND DATA ANALYSIS and co-editor of STATISTICAL CASE STUDIES: A COLLABORATION BETWEEN ACADEME AND INDUSTRY. She currently serves as the chair of the ASA's Section on Statistical Education and is a member of the joint ASA/NCTM Committee on Curriculum in Statistics and Probability for Grades K-12. Additionally, Roxy was the editor of the new edition of STATISTICS: A GUIDE TO THE UNKNOWN. This book contains 25 essays that showcase the use of statistics in a wide variety of disciplines.

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Table of Contents


1. THE ROLE OF STATISTICS. Three Reasons to Study Statistics. The Nature and Role of Variability. Statistics and Data Analysis. Types of Data and Simple Graphical Displays. Chapter Activities. Supplementary Exercises. 2. THE DATA ANALYSIS PROCESS AND COLLECTING DATA SENSIBLY. The Data Analysis Process. Sampling. Statistical Studies: Observation and Experimentation. Simple Comparative Experiments. More on Experimental Design. More on Observational Studies: Designing Surveys (Optional). Communicating and Interpreting the Results of Statistical Analyses. Chapter Activities/ Supplementary Exercises. 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. Chapter Activities. Supplementary Exercises. 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. Chapter Activities. Supplementary Exercises. 5. SUMMARIZING BIVARIATE DATA. Correlation. Linear Regression: Fitting a Line to Bivariate Data. Assessing the Fit of a Line. Nonlinear Relationships and Transformations. Communicating and Interpreting the Results of Statistical Analyses. Chapter Activities. Supplementary Exercises. 6. PROBABILITY. Interpreting Probabilities and Basic Probability Rules. Probability as a Basis for Making Decisions. Estimating Probabilities. Empirically and by Using Simulation. Chapter Activities. Supplementary Exercises. 7. POPULATION DISTRIBUTIONS. Describing the Distribution of Values in a Population. Population Models for Continuous Numerical Variables. Normal Distributions. Checking Normality and Normalizing Transformations. Chapter Activities. Supplementary Exercises. 8. SAMPLING VARIABILITY AND SAMPLING DISTRIBUTIONS. Statistics and Sampling Variability. The Sampling Distribution of a Sample Mean. The Sampling Distribution of a Sample Proportion. Chapter Activities. Supplementary Exercises. Graphing Calculator Explorations. 9. ESTIMATION USING A SINGLE SAMPLE. Point Estimation. A Large-Sample Confidence Interval for a Population Proportion. A Confidence Interval for a Population Mean. Communicating and Interpreting the Results of a Statistical Analyses. Chapter Activities. Supplementary Exercises. 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. Chapter Activities. Supplementary Exercises. 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. Distribution-Free Procedures for Inferences Concerning a Difference Between Two Population or Treatment Means Using Independent Samples (Optional). Communicating and Interpreting the Results of Statistical Analyses. Chapter Activities. Supplementary Exercises. Graphing Calculator Explorations. 12. THE ANALYSIS OF CATEGORICAL DATA AND GOODNESS-OF-FIT TESTS. Chi-Square Tests for Univariate Categorical Data. Test for Homogeneity and Independence in a Two-Way Table. Communicating and Interpreting the Results of Statistical Analyses. Chapter Activities. Supplementary Exercises. Graphing Calculator Explorations. 13. SIMPLE LINEAR REGRESSION AND CORRELATION: INFERENTIAL METHODS. The Simple Linear Regression Model. Inferences Concerning the Slope of the Population Regression Line. Checking Model Adequacy. Inferences Based on the Estimated Regression Line. Inferences About the Population Correlation Coefficient (Optional). Communicating and Interpreting the Results of Statistical Analyses. Chapter Activities. Supplementary Exercises. Graphing Calculator Explorations. 14. MULTIPLE REGRESSION ANALYSIS. Multiple Regression Models. Fitting a Model and Assessing Its Utility. Inferences Based on an Estimated Model. Other Issues in Multiple Regression. Communicating and Interpreting the Results of Statistical Analyses. Chapter Activities. Supplementary Exercises. 15. THE ANALYSIS OF VARIANCE. Single-Factor ANOVA and the F Test. Multiple Comparisons. The F Test for a Randomized Block Experiment. Two-Factor ANOVA. Communicating and Interpreting the Results of Statistical Analyses. Appendix: ANOVA Computations. Chapter Activities. Supplementary Exercises. Graphing Calculator Explorations. Appendices. Appendix I: The Binomial Distribution. Appendix II: Statistical Tables.
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