JMP for Basic Univariate and Multivariate Statistics: A Step-by-step Guide
Doing statistics in JMP has never been easier! Learn how to manage JMP data and perform the statistical analyses most commonly used in research in the social sciences and other fields with JMP for Basic Univariate and Multivariate Statistics: A Step-by-Step Guide, authored by Ann Lehman, Norm O'Rourke, Larry Hatcher, and Edward Stepanski. Clearly written instructions guide you through the basic concepts of research and data analysis, enabling you to easily perform statistical analyses and solve problems in real-world research. Step by step, you'll discover how to obtain descriptive and inferential statistics, summarize results, perform a wide range of JMP analyses, interpret the results, and more. Topics include: screening data for errors and selecting subsets with the JMP Distribution platform, computing the coefficient alpha reliability index (Cronbach's alpha) for a multiple-item scale, performing bivariate analyses for all types of variables, performing a one-way analysis of variance (ANOVA), performing a multiple regression, and using the JMP Fit Model platform to perform a one-way multivariate analysis of variance (MANOVA). This user-friendly book introduces researchers and students of the social sciences to JMP and to elementary statistical procedures, while more advanced statistical procedures that are presented make it an invaluable reference guide for experienced researchers as well.
