JMPer Cable Current Issue (Spring 2008)
Cover Story: Discriminant Analysis: Pathological Gambling
By Tonya Mauldin, SAS Institute Technical Support
Suppose you want to evaluate a 12-item questionnaire that is designed to identify various levels of gambling behavior. The questions are based on DSM-IV® diagnostic criteria for pathological gambling (DSM-IV-TR, 2000). This reference is the diagnostic and statistical manual of mental disorders for mental professionals that lists different categories of mental disorders and the criteria for diagnosing them.
Download the data sets referenced in the article.
Finding Sample Data (Pg. 4)
By Lee Creighton, JMP Development
New JMP 7 training courses include JMP Software: Statistical Data Exploration, JMP Software: ANOVA and Regression, JMP Software: Introduction to the JMP Scripting Language (JSL), and more.
When reading reference guides or teaching a JMP class, it is often important to quickly locate the sample data installed with JMP.
Statistical Intervals: Confidence, Prediction, Enclosure (Pg. 5)
By José G. Ramírez, Ph.D., W.L. Gore and Associates, Inc.
This article uses an example to explain three kinds of statistical intervals that can be confusing, even in the minds of those who use them often: confidence intervals, prediction intervals, and tolerance intervals.
Download the data set referenced in the article.
Book Discussion: Elementary Statistics Using JMP (Pg. 8)
By Sandra Schlotzhauer
Published by SAS Publishing, April 2007
This reader-friendly guide bridges the gap between statistics texts and JMP documentation. The book begins opens with an explanation of the basics of JMP data tables, demonstrating how to use JMP for descriptive statistics and graphs. The author continues with a lucid discussion of fundamental statistical concepts, including normality and hypothesis testing.
Discovery 2008: The Data Exploration Conference, June 16-17 (Pg. 8)
Formerly the JMP User Conference, Discovery 2008 offers a chance to explore new dimensions in modeling and data visualization. The conference this year will focus on how SAS and JMP are at work together in corporate, academic, government and research settings to make discoveries through data visualization.
Why Shouldn’t I Delete That Model Term? (Pg. 9)
By Mark Bailey and Laura Ryan, SAS Institute Education
Students are often told that certain terms that should not be deleted from a linear regression model. On the other hand, using the simplest, most parsimonious model means that all non-significant terms should be removed.
Download the data sets referenced in the article.
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