Real World Data Sets with new problems along with ARIS, McGraw-Hill's Homework Management System, define what this second edition has to offer. Within ARIS, Navidi offers 300 algorithmic practice problems along with Java applets that allow students to interactively explore ideas in the text. Customizable PowerPoint lecture notes for each chapter are available as well, along with suggested syllabi, and other features. More information can be found at aris.mhhe.com.
This new edition includes more than 200 new exercises, a new section on point estimation on histograms, and provides discussion of Chebyshev’s inequality.
William Navidi is Professor of Mathematical and Computer Sciences at the Colorado School of Mines. He received the B.A. degree in mathematics from New College, the M.A. in mathematics from Michigan State University, and the Ph.D. in statistics from the University of California at Berkeley. Professor Navidi has authored more than 50 research papers both in statistical theory and in a wide variety of applications including computer networks, epidemiology, molecular biology, chemical engineering, and geophysics.
1 Sampling and Descriptive Statistics
3 Propagation of Error
4 Commonly Used Distributions
5 Confidence Intervals
6 Hypothesis Testing
7 Correlation and Simple Linear Regression
8 Multiple Regression
9 Factorial Experiments
10 Statistical Quality Control
B Partial Derivatives
C Suggestions for Further Reading
Answers to Selected Exercises