Synopses & Reviews
Real data and real examples make statistics real for you! Discover the importance of statistics and how the practice affects your life and the world around you with STATISTICS: THE EXPLORATION AND ANALYSIS OF DATA. Authors Devore and Peck have helped thousands of students master statistical concepts and learn to apply them. Using real data, the authors show you how statistical techniques are used with increasing frequency in a variety of fields, including business, medicine, social sciences, and applied sciences such as engineering. Their accessible writing style is enhanced by numerous examples, including hands-on activities and "Seeing Statistics" applets. Plus, you can chart your own path to success with StatisticsNOW, the personalized online learning companion, and Personal Tutor with SMARTHINKING, which gives you access to live online tutoring!
Synopsis
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.
About 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 Oberlin College, and has had visiting appointments at Stanford, Harvard, the University of Washington, and New York University. Jay is currently Professor and Chair of the Statistics Department at Cal Poly, San Luis Obispo, California. The Statistics Department at Cal Poly has an international reputation for activities in statistics education. In addition to this book, Professor Devore has authored several widely used engineering statistics texts, and is currently working on a book in applied mathematical statistics. 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 far away places. He is especially proud of his wife Carol, a retired elementary school teacher, his daughter Allison, who works for the Center for Women and Excellence in Boston, and his daughter Teri, who is finishing a graduate program in education at NYU.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.
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.