Introduction to Statistics and Data Analysis (with CD-ROM and Internet Companion) [Hardcover]

Roxy Peck (Author), Chris Olsen (Author), Jay L. Devore (Author)

Book Description

ISBN-10: 0534467105 | ISBN-13: 978-0534467104 | Publication Date: March 3, 2004 | Edition: 2

Roxy Peck, Chris Olsen and Jay Devore's new edition uses real data and attention-grabbing examples to introduce students to the study of statistical output and methods of data analysis. Based on the best-selling STATISTICS: THE EXPLORATION AND ANALYSIS OF DATA, Fifth Edition, this new INTRODUCTION TO STATISTICS AND DATA ANALYSIS, Second Edition integrates 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. Conceptual comprehension is cemented by the simplicity of notation--frequently substituting words for symbols. Simple notation helps students grasp concepts. Hands-on activities and Seeing Statistics applets in each chapter allow students to practice statistics firsthand.

Editorial Reviews

Review

1. THE ROLE OF STATISTICS AND THE DATA ANALYSIS PROCESS. Why Study Statistics. The Nature and Role of Variability. Statistics and the Data Analysis Process. Types of Data and Some Simple Graphical Displays. 2. COLLECTING DATA SENSIBLY. Statistical Studies: Observation and Experimentation. Sampling. Simple Comparative Experiments. More on Experimental Design. More on Observational Studies: Designing Surveys (Optional). Interpreting and Communicating the Results of Statistical Analyses. 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. Interpreting and Communicating the Results of Statistical Analyses. 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. Interpreting and Communicating the Results of Statistical Analyses. 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). Interpreting and Communicating the Results of Statistical Analyses. 6. PROBABILITY. Chance Experiments and Events. Definition of Probability. Basic Properties of Probability. Conditional Probability. Independence. Some General Probability Rules. Estimating Probabilities Empirically Using Simulation. 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. Binomial and Geometric Distributions. Normal Distributions. Checking for Normality and Normalizing Transformations. Using the Normal Distribution to Approximate a Discrete Distribution. 8. SAMPLING VARIABILITY AND SAMPLING DISTRIBUTION. Statistics and Sampling Variability. The Sampling Distribution of a Sample Mean. The Sampling Distribution of a Sample Proportion. 9. ESTIMATION USING A SINGLE SAMPLE. Point Estimation. Large-Sample Confidence Interval for a Population Proportion. Confidence Interval for a Population Mean. Interpreting and Communicating the Results of Statistical Analyses. 10. HYPOTHESIS TESTING USING A SINGLE SAMPLE. Hypotheses and Test Procedures. Errors in Hypotheses Testing. Large-Sample Hypothesis Tests for a Population Proportion. Hypotheses Tests for a Population Mean. Power and Probability of Type II Error. Interpreting and Communicating the Results of Statistical Analyses. 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. Interpreting and Communicating the Results of Statistical Analyses. 12. THE ANALYSIS OF CATEGORICAL DATA AND GOODNESS-OF-FIT TESTS. Chi-Square Tests for Univariate Data. Tests for Homogeneity and Independence in a Two-way Table. Interpreting and Communicating the Results of Statistical Analyses. 13. SIMPLE LINEAR REGRESSION AND CORRELATION: INFERENTIAL METHODS. 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). Interpreting and Communicating the Results of Statistical Analyses. 14. MULTIPLE REGRESSION ANALYSIS. Multiple Regression Models. Fitting a Model and Assessing Its Utility. Inferences Based on an Estimated Model (online). Other Issues in Multiple Regression (online). Interpreting and Communicating 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). Interpreting and Communicating the Results of Statistical Analyses (online). 16. NONPARAMETRIC (DISTRIBUTION-FREE STATISTICAL METHODS (ONLINE). Distribution-Free Procedures for Inferences About a Difference Between Two Population or Treatment Means Using Independent Samples (Optional). Distribution-Free Procedures for Inferences About a Difference Between Two Population or Treatment Means Using Paired Samples. Distribution-Free ANOVA.

About the Author

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 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 Devore received a BS in Engineering Science from UC Berkeley and a PhD 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. Jay has previously authored five other books, including PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, currently in its 6th edition. 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.

Product Details

• Hardcover: 912 pages
• Publisher: Duxbury Press; 2 edition (March 3, 2004)
• Language: English
• ISBN-10: 0534467105
• ISBN-13: 978-0534467104
• Product Dimensions: 9.9 x 7.9 x 1.4 inches
• Shipping Weight: 3.9 pounds
• Average Customer Review: 4.5 out of 5 stars  See all reviews (2 customer reviews)
• Amazon Best Sellers Rank: #1,021,695 in Books (See Top 100 in Books)

Customer Reviews

Most Helpful Customer Reviews

12 of 13 people found the following review helpful:

5.0 out of 5 stars Recommended by Authors for Fuller Treatment of Probability, November 14, 2006

By 

Karl M. Bunday (Minnetonka, MN USA) - See all my reviews
(REAL NAME)   

This review is from: Introduction to Statistics and Data Analysis (Hardcover)

The authors are renowned for their work in producing clear, modern, thought-provoking statistics textbooks. This book differs from Statistics: The Exploration and Analysis of Data, 5th Ed. in that it has a more expansive discussion of probability. It also differs from that title in having more specific calculator exercises, but has the same great features of all editions of all textbooks from the same authors. Prefer this title to Statistics: The Exploration and Analysis of Data, 5th Ed. if you want more detail and depth on probability, and more practice with using an electronic calculator to explore statistics.

2 of 9 people found the following review helpful:

4.0 out of 5 stars expensive but a good deal, March 1, 2007

By 

Lauren Bonney - See all my reviews
(REAL NAME)   

This review is from: Introduction to Statistics and Data Analysis (Hardcover)

This book came quickly and was the correct version of the one I needed for my class. It was about $40 less expensive on Amazon than it was at my university's bookstore, but it's still a lot of money. I'm not sure if it's my computer or the CD, but I can't get the SPSS program to run. Overall, this book/CD was what I expected it to be at a relatively good price.