Synopses & Reviews
UNDERSTANDABLE STATISTICS is a thorough, yet accessible program designed to help students overcome their apprehensions about statistics. The authors provide guidance and informal advice, while showing students the links between statistics and the world. To reinforce this approach, the book integrates real-life data from a variety of sources including journals, periodicals, newspapers, and the Internet. The Ninth Edition addresses the growing importance of developing students' critical thinking and statistical literacy skills through the introduction of new features and exercises throughout the text. Extensive technology resources include a new algorithmic test bank and lecture slides, along with a market-leading DVD series and other resources designed to provide reinforcement for students and support for instructors. The use of graphing calculators, Excel, Minitab, and SPSS is covered though not required.
Synopsis
UNDERSTANDABLE STATISTICS: CONCEPTS AND METHODS, Tenth Edition, is a thorough, yet accessible program designed to help readers overcome their apprehensions about statistics. The authors provide clear guidance and informal advice while showing the links between statistics and the world. To reinforce this approach--and make the material interesting as well as easier to understand--the book integrates real-life data from a variety of sources, including journals, periodicals, newspapers, and the Internet. Readers also have opportunities to develop their critical thinking and statistical literacy skills through special features and exercises throughout the text. The use of graphing calculators, Excel, MINITAB, and SPSS is covered for those who wish to learn about these helpful tools.
About the Author
Charles Brase has more than 30 years of full-time teaching experience in mathematics and statistics. He taught at the University of Hawaii, Manoa Campus, for several years and at Regis University in Denver, Colorado, for more than 28 years. Charles received the Excellence in Teaching award from the University of Hawaii and the Faculty Member of the Year award from Regis University on two occasions. He earned degrees from the University of Colorado, Boulder, and has a Ph.D. in Mathematics, an M.A. in Mathematics, and a B.A. in Physics. Corrinne Pellillo Brase has taught at Hawaii Pacific College, Honolulu Community College, and Arapahoe Community College in Littleton, Colorado. She was also involved in the mathematics component of an equal opportunity program at the University of Colorado. Corrinne received the Faculty of the Year award from Arapahoe Community College. She earned degrees from the University of Colorado, Boulder, and has an M.A. and B.A. in Mathematics.
Table of Contents
Note: Each chapter concludes with a Summary, Important Words and Symbols, Chapter Review Problems, Data Highlights: Group Projects, Linking Concepts: Writing Projects, and Using Technology. Table of Prerequisite Material. 1. GETTING STARTED. Focus Problem: Where Have All the Fireflies Gone? What Is Statistics. Random Samples. Introduction to Experimental Design. 2. ORGANIZING DATA. Focus Problem: Say It with Pictures. Frequency Distributions, Histograms, and Related Topics. Bar Graphs, Circle Graphs, and Time-Series Graphs. Stem-and-Leaf Displays. 3. AVERAGES AND VARIATION. Focus Problem: The Educational Advantage. Measures of Central Tendency: Mode, Mediate, and Mean. Measures of Variation. Percentiles and Box-and-Whisker Plots. Cumulative Review Problems: Chapters 1-3. 4. ELEMENTARY PROBABILITY THEORY. Focus Problem: How Often Do Lie Detectors Lie? What Is Probability? Some Probability Rules--Compound Events. Trees and Counting Techniques. 5. THE BINOMIAL PROBABILITY DISTRIBUTION AND RELATED TOPICS. Focus Problem: Personality Preference Types: Introvert or Extrovert? Introduction to Random Variables and Probability Distributions. Binomial Probabilities. Additional Properties of the Binomial Distribution. The Geometric and Poisson Probability Distributions. 6. NORMAL DISTRIBUTIONS. Focus Problem: Impulse Buying. Graphs of Normal Probability Distributions. Standard Units and Areas Under the Standard Normal Distribution. Areas Under Any Normal Curve. Normal Approximation to the Binomial Distribution. Sampling Distributions. The Central Limit Theorem. Cumulative Review Problems: Chapters 4-6. 7. ESTIMATION. Focus Problem: The Trouble with Wood Ducks. Estimating µ When ? ?Is Known. Estimating µ When ? Is Unknown. Estimating p in the Binomial Distribution. Estimating µ 1-µ 2 and p1-p2. 8. HYPOTHESIS TESTING. Focus Problem: Benford's Law: The Importance of Being Number 1. Introduction to Statistical Tests. Testing the Mean µ. Testing a Proportion p. Tests Involving Paired Differences (Dependent Samples). Testing µ1-µ2 and p1-p2 (Independent Samples). 9. CORRELATION AND REGRESSION. Focus Problem: Changing Populations and Crime Rate. Scatter Diagrams and Linear Correlation. Linear Regression and the Coefficient of Determination. Inferences for Correlation and Regression. Multiple Regression. Cumulative Review Problems: Chapters 7-9. 10. CHI-SQUARE AND F DISTRIBUTIONS. Focus Problem: Archaeology in Bandelier National Monument. Part I: Inferences Using the Chi-Square Distribution. Overview of the Chi-Square Distribution. Chi-Square: Tests of Independence and of Homogeneity. Chi-Square: Goodness of Fit. Testing and Estimating a Single Variance or Standard Deviation. Part II: Inferences Using the F Distribution. Testing Two Variances. One-Way ANOVA: Comparing Several Sample Means. Introduction to Two-Way ANOVA. 11. NONPARAMETRIC STATISTICS. Focus Problem: How Cold? Compared to What? The Sign Test for Matched Pairs. The Rank-Sum Test. Spearman Rank Correlation. Runs Test for Randomness. Cumulative Review Problems: Chapters 10-12. APPENDIX I: ADDITIONAL TOPICS. Bayes's Theorem. The Hypergeometric Probability Distribution. APPENDIX II: TABLES. Random Numbers. Binomial Coefficients. Binomial Probability Distribution. Poisson Probability Distribution. Areas of a Standard Normal Distribution. Critical Values for Student's t Distribution. The X2 Distribution. Critical Values for F Distribution. Critical Values for Spearman Rank Correlation. Critical Values for Number of Runs R.