Statistical Analysis for Business Using JMP: A Student's Guide

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SAS Institute, 2011 - Computers - 380 pages
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Statistical Analysis for Business Using JMP: A Student's Guide by Willbann D. Terpening is a complete and thorough introduction to business statistics using JMP. While the book is designed for introductory business statistics courses at the undergraduate or MBA level, industry professionals wanting to brush up on their knowledge of statistics and those wanting an introduction to using JMP for statistical analysis will also find it useful. The book starts with an introduction to using JMP in statistical analysis, basic descriptive statistics and graphical analysis, and the fundamentals of inferential statistics. It then covers more advanced topics in inferential statistics organized around the analysis platforms of JMP. Topics include the effects of a qualitative variable on a quantitative variable (two group tests and analysis of variance), the effects of a qualitative variable on a qualitative variable (chi-square and contingency tables), the effects of a quantitative variable on a quantitative variable (simple regression and correlation), and the effects of a quantitative variable on a qualitative variable (logistic and multinomial regression). The final chapter provides an introduction to multivariate statistics and multiple regression.
 

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Contents

Descriptive Statistics
65
Part 3 Basic Foundation
135
Part 4 The Effects of One Variable on Another
213
Multiple Regression
309
Index
353
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About the author (2011)

Willbann Terpening is Professor of Operations Management in the School of Business Administration at Gonzaga University, where he teaches graduate and undergraduate courses in business statistics, process management and improvement, and spreadsheet modeling. In addition, he does research in the general areas of measurement and research methods. The author or coauthor of many books, journal articles, and software packages, he received his Ph.D. in quantitative psychology from Southern Illinois University. Will is a member of the Production and Operations Management Society, the Academy of Management, the Decision Sciences Institute, and the American Statistical Association.

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