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Statistics The Exploration and Analysis of Data

ISBN-10: 0495390879
ISBN-13: 9780495390879
Edition: 6th 2008
Authors: Roxy Peck, Jay DeVore
List price: $343.95
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Description: This book introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you through an intuition-based learning process that stresses interpretation and communication of statistical  More...

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Book details

List price: $343.95
Edition: 6th
Copyright year: 2008
Publisher: Brooks/Cole
Publication date: 7/18/2007
Binding: Hardcover
Pages: 736
Size: 8.75" wide x 10.00" long x 1.25" tall
Weight: 3.982
Language: English

This book introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you through an intuition-based learning process that stresses interpretation and communication of statistical information. They help you grasp concepts and cement your comprehension by using simple notation?frequently substituting words for symbols.

Roxy Peck is Emerita Associate Dean of the College of Science and Mathematics and Professor of Statistics Emerita at California Polytechnic State University, San Luis Obispo. A faculty member at Cal Poly from 1979 until 2009, Roxy served for six years as Chair of the Statistics Department before becoming Associate Dean, a position she held for 13 years. She received an M.S. in Mathematics and a Ph.D. in Applied Statistics from the University of California, Riverside. Roxy is nationally known in the area of statistics education, and she was presented with the Lifetime Achievement Award in Statistics Education at the U.S. Conference on Teaching Statistics in 2009. 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. Roxy served for five years as the Chief Reader for the Advanced Placement Statistics Exam and has chaired 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 and the Section on Statistics Education. In addition to her texts in introductory statistics, Roxy is also co-editor of "Statistical Case Studies: A Collaboration Between Academe and Industry" and a member of the editorial board for "Statistics: A Guide to the Unknown, 4th Edition." Outside the classroom, Roxy likes to travel and spends her spare time reading mystery novels. She also collects Navajo rugs and heads to Arizona and New Mexico whenever she can find the time.

Jay Devore is Professor Emeritus of Statistics at California Polytechnic State University. He 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. Jay 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, he served as Chair of the Statistics Department. In addition to this book, Jay has written several widely used engineering statistics texts and a book in applied mathematical statistics. He recently coauthored a text in probability and stochastic processes. He is the recipient of a distinguished teaching award from Cal Poly, is a Fellow of the American Statistical Association , and has served several terms as an Associate Editor of the "Journal 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, who has held several high-level positions in nonprofit organizations in Boston and New York City, and his daughter Teresa, an ESL teacher in New York City.

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
Collecting Data Sensibly
Statistical Studies: Observation and Experimentation
Sampling
Simple Comparative Experiments
More Experimental Design
More on Observational Studies: Designing Surveys
Interpreting and Communicating the Results of Statistical Analyses
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
Numerical Methods for Describing Data
Describing the Center of a Data Set
Describing the 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
Summarizing Bivariate Data
Correlation
Linear Regression: Fitting a Line to Bivariate Data
Assessing the Fit of a Line
Nonlinear Relationship and Transformations
Logistic Regression
Interpreting and Communicating the Results of Statistical Analyses
Probability
Interpreting Probabilities and Basic Probability Rules
Probability as a Basis for Making Decisions
Estimating Probabilities Empirically and by Using Simulation
Population Distributions
Describing the Distribution of Values in a Population
Population Models for Continuous Numerical Variables
Normal Distributions
Checking for Normality and Normalizing Transformations
Sampling Variability and Sampling Distributions
Statistics and Sampling Variability
The Sampling Distribution of a Sample Mean
The Sampling Distribution of a Sample Proportion
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
Hypotheses Testing Using a Single Sample
Hypotheses and Test Procedures
Errors in Hypothesis Testing
Large-Sample Hypothesis Tests for a Population Proportion
Hypothesis Test for a Population Mean
Power and Probability of Type II Error
Interpreting and Communicating the Results of Statistical Analyses
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
The Analysis of Categorical Data and Doogness-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
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
Inferences About the Population Correlation Coefficient
Interpreting and Communicating the Results of Statistical Analyses
Multiple Regression Analysis
Multiple Regression Models
Fitting a Model and Assessing Its Utility
Inferences Based on an Estimated Model
Other Issues in Multiple Regression
Interpreting and C

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