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« JMP 14 Multivariate Methods describes techniques for analyzing several variables simultaneously. The book covers descriptive measures, such as correlations. It also describes methods that give insight into the structure of the multivariate data, such as clustering, latent class analysis, principal components, discriminant analysis, and partial least squares. »--
« JMP 14 Fitting Linear Models focuses on the Fit Model platform and many of its personalities. Linear and logistic regression, analysis of variance and covariance, and stepwise procedures are covered. Also included are multivariate analysis of variance, mixed models, generalized models, and models based on penalized regression techniques. »--
This book provides hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use the intuitive interface for data analysis in JMP. Each chapter features concept-specific tutorials, examples, brief reviews of concepts, step-by-step illustrations, and exercises. Updated for JMP 13, JMP Start Statistics, Sixth Edition includes many new features, including: The redesigned Formula Editor. New and improved ways to create formulas in JMP directly from the data table or dialogs. Interface updates, including improved menu layout. Updates and enhancements in many analysis platforms. New ways to get data into JMP and to save and share JMP results. Many new features that make it easier to use JMP.
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: Methods for Researchers and Social Scientists, Second Edition. Updated for JMP 10 and including new features on the statistical platforms, this book offers clearly written instructions to 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 clearly in a way that is suitable for publication, perform a wide range of JMP analyses, interpret the results, and more. Topics include screening data for errors selecting subsets 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), multiple regression, and a one-way multivariate analysis of variance (MANOVA) Advanced topics include analyzing models with interactions and repeated measures. There is also comprehensive coverage of principle components with emphasis on graphical interpretation. This user-friendly book introduces researchers and students of the social sciences to JMP and to elementary statistical procedures, while the more advanced statistical procedures that are presented make it an invaluable reference guide for experienced researchers as well.
Going beyond the theoretical foundation, this step-by-step book gives you the technical knowledge and problem-solving skills that you need to perform real-world multivariate data analysis. --
Using JMP statistical discovery software from SAS, Discovering Partial Least Squares with JMP explores Partial Least Squares and positions it within the more general context of multivariate analysis. This book motivates current and potential users of JMP to extend their analytical repertoire by embracing PLS. Dynamically interacting with JMP, you will develop confidence as you explore underlying concepts and work through the examples. The authors provide background and guidance to support and empower you on this journey.
"Practical Data Analysis with JMP" uses the powerful interactive and visual approach of JMP to introduce readers to the logic and methods of statistical thinking and data analysis. The book can stand on its own or be used to supplement a standard introduction-to-statistics textbook.
Discover the power of mixed models with JMP and JMP Pro. Mixed models are now the mainstream method of choice for analyzing experimental data. Why? They are arguably the most straightforward and powerful way to handle correlated observations in designed experiments. Reaching well beyond standard linear models, mixed models enable you to make accurate and precise inferences about your experiments and to gain deeper understanding of sources of signal and noise in the system under study. Well-formed fixed and random effects generalize well and help you make the best data-driven decisions. JMP for Mixed Models brings together two of the strongest traditions in SAS software: mixed models and JMP. JMP's groundbreaking philosophy of tight integration of statistics with dynamic graphics is an ideal milieu within which to learn and apply mixed models, also known as hierarchical linear or multilevel models. If you are a scientist or engineer, the methods described herein can revolutionize how you analyze experimental data without the need to write code. Inside you'll find a rich collection of examples and a step-by-step approach to mixed model mastery. Topics include: Learning how to appropriately recognize, set up, and interpret fixed and random effects Extending analysis of variance (ANOVA) and linear regression to numerous mixed model designs Understanding how degrees of freedom work using Skeleton ANOVA Analyzing randomized block, split-plot, longitudinal, and repeated measures designs Introducing more advanced methods such as spatial covariance and generalized linear mixed models Simulating mixed models to assess power and other important sampling characteristics Providing a solid framework for understanding statistical modeling in general Improving perspective on modern dilemmas around Bayesian methods, p-values, and causal inference
Building Better Models with JMP® Pro provides an example-based introduction to business analytics, with a proven process that guides you in the application of modeling tools and concepts. It gives you the "what, why, and how" of using JMP® Pro for building and applying analytic models. This book is designed for business analysts, managers, and practitioners who may not have a solid statistical background, but need to be able to readily apply analytic methods to solve business problems. In addition, this book will greatly benefit faculty members who teach any of the following subjects at the lower to upper graduate level: predictive modeling, data mining, and business analytics. Novice to advanced users in business statistics, business analytics, and predictive modeling will find that it provides a peek inside the black box of algorithms and the methods used. Topics include: regression, logistic regression, classification and regression trees, neural networks, model cross-validation, model comparison and selection, and data reduction techniques. Full of rich examples, Building Better Models with JMP Pro is an applied book on business analytics and modeling that introduces a simple methodology for managing and executing analytics projects. No prior experience with JMP is needed. Make more informed decisions from your data using this newest JMP book.
Achieve best-in-class metrics and get more from your data with JMP JMP Connections is the small- and medium-sized business owner's guide to exceeding customer expectations by getting more out of your data using JMP. Uniquely bifunctional, this book is divided into two parts: the first half of the book shows you what JMP can do for you. You'll discover how to wring every last drop of insight out of your data, and let JMP parse reams of raw numbers into actionable insight that leads to better strategic decisions. You'll also discover why it works so well; clear explanations break down the Connectivity platform and metrics in business terms to demystify data analysis and JMP while giving you a macro view of the benefits that come from optimal implementation. The second half of the book is for your technical team, demonstrating how to implement specific solutions relating to data set development and data virtualization. In the end, your organization reduces Full Time Equivalents while increasing productivity and competitiveness. JMP is a powerful tool for business, but many organizations aren't even scratching the surface of what their data can do for them. This book provides the information and technical guidance your business needs to achieve more. Learn what a JMP Connectivity Platform can do for your business Understand Metrics-on-Demand, Real-Time Metrics, and their implementation Delve into technical implementation with information on configuration and management, version control, data visualization, and more Make better business decisions by getting more and better information from your data Business leadership relies on good information to make good business decisions—but what if you could increase the quality of the information you receive, while getting more of what you want to know and less of what you don't need to know? How would that affect strategy, operations, customer experience, and other critical areas? JMP can help with that, and JMP Connections provides real, actionable guidance on getting more out of JMP.