Statistical Techniques in Business and Economics ISE

Douglas A. Lind earned his B.S. in Business from Bowling Green State University, and his Ph.D. and M.B.A. from the University of Toledo. He is Emeritus Professor at Coastal Carolina University and the University of Toledo. Dr. Lind is a co-author of Statistical Techniques in Business and Economics with the late Robert D. Mason and William G. Marchal. He has more than 38 years of college teaching experience, including teaching statistics at the introductory, intermediate, and advanced undergraduate levels, as well as graduate courses in statistics and research methods. Dr. Lind is a past recipient of the Tony DeJute Outstanding Teacher Award. William G. Marchal earned his B.S. in mathematics from the University of Dayton, his M.A. in mathematics from Catholic University of America, and his D.Sc. in operations research from George Washington University. He is Emeritus Professor of Information Systems and Operations Management at the University of Toledo College of Business Administration. Dr. Marchal has held visiting appointments at the University of Michigan and at George Mason University. He has worked at the Executive Office of the District of Columbia government, the George Washington University Institute for Management Science, and the U.S. Army Chemical Research and Development Center. He has also served as an associate editor of Naval Research Logistics. Samuel A. Wathen earned his B.S. in forestry from the University of Illinois, an M.B.A. from Oklahoma State University, an M.S. in forest biometrics from Virginia Polytechnic Institute and State University, and his Ph.D. in business administration from the University of Minnesota. He is Distinguished Professor Emeritus of Management and Decision Sciences in the E. Craig Wall Sr. College of Business Administration at Coastal Carolina University. Dr. Wathen's research interests include applied statistics, teaching methods, and manufacturing and service process design. Most recently, he published the article “Using Real‐Life Major League Baseball Data in an Introductory Statistics Course” in the Decision Sciences Journal of Innovative Education.

• 1 What Is Statistics? 2 Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation 3 Describing Data: Numerical Measures 4 Describing Data: Displaying and Exploring Data 5 A Survey of Probability Concepts 6 Discrete Probability Distributions 7 Continuous Probability Distributions 8 Sampling, Sampling Methods, and the Central Limit Theorem 9 Estimation and Confidence Intervals 10 One-Sample Tests of Hypothesis 11 Two-Sample Tests of Hypothesis 12 Analysis of Variance 13 Correlation and Linear Regression 14 Multiple Regression Analysis 15 Nonparametric Methods Nominal Level Hypothesis Tests 16 Nonparametric Methods: Analysis of Ordinal Data 17 Index Numbers 18 Forecasting with Time Series Analysis 19 Statistical Process Control and Quality Management 20 An Introduction to Decision Theory (Online Only) Appendixes Appendixes, Data Sets, Tables, Software Commands, Answers