Discovering JMP 11 provides a basic introduction to using JMP. For new users of JMP, this is a great place to start. The book also includes details about importing your data into JMP, analyzing the data, and sharing the results.

JMP 11 Basic Analysis covers the initial types of analyses that you often perform in JMP, such as univariate, bivariate, and oneway analyses. Creating tables of summary statistics with the Tabulate platform is included along with approximating sampling distributions using bootstrapping.

JMP 11 Consumer Research focuses on analyses that help users observe and predict subject's behavior, particularly those in the market research field. The Uplift platform predicts consumer behavior based on shifts in marketing efforts. Learn how to tabulate and summarize categorical responses with the Categorical platform. Factor Analysis rotates principal components to help identify which directions have the most variation among the variables. The book also covers Item Analysis, a method for identifying latent traits that might affect an individual's choices. And read about the Choice platform, which market researchers use to estimate probability in consumer spending.

The JMP 11 Design of Experiments Guide covers classic DOE designs (for example, full factorial, response surface, and mixture designs). Read about more flexible custom designs, which you generate to fit your particular experimental situation. And discover JMP's definitive screening designs, an efficient way to identify important factor interactions using fewer runs than required by traditional designs. The book also provides guidance on determining an appropriate sample size for your study.

Start with JMP 11 Essential Graphing to find the ideal graph for your data. The book begins with Graph Builder, a quick way to create graphs in a drag-and-drop window. Line charts, ellipses, box plots, and maps are just a few of the graphs available in Graph Builder. Find information about creating other types of plots: bubble plots, scatterplots, parallel plots, and more.

JMP 11 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.

The JMP 11 JSL Syntax Reference focuses on functions and their arguments, and messages that you send to objects and display boxes. Notes and examples are included.

Whether your model is deterministic, or involves necessary “noise” as well as a “signal,” JMP is equipped to handle your modeling needs. JMP 11 Multivariate Methods shows you how to take advantage of the modeling platforms Multivariate, Cluster, Discriminant, Principal Components, and Partial Least Squares.

JMP 11 Profilers covers the family of interactive profiling tools, which enable you to view cross-sections of any response surface. The book also includes details about plotting points and surfaces in a three-dimensional graph. JMP 11 Profilers covers the family of interactive profiling tools, which enable you to view cross-sections of any response surface. The book also includes details about plotting points and surfaces in a three-dimensional graph.

Quality and Process Methods describes tools for evaluating and improving processes. The book begins by discussing creating control charts, which let you visualize process measurements over time, quantify common cause variation, and identify special cause variation. Details about estimating your process capability based on measurement systems analysis studies are included. Lastly, the book discusses Pareto plots and cause-and-effect diagrams to identify root causes of variability.

JMP 11 Reliability and Survival Methods provides details about evaluating and improving reliability in a product or system and analyzing survival data for people and products. The book explains how to fit the best distribution to your time-to-event data or analyze destruction data. A few other topics include analyzing competing causes of failure, modeling reliability as improvements are made over time, and analyzing recurring events.

Scripting Guide provides details for taking advantage of the powerful JMP Scripting Language (JSL). Learn how to write and debug scripts, manipulate data tables, construct display boxes, create JMP applications, and more.

JMP 11 Specialized Models provides details about modeling techniques such as partitioning, neural networks, nonlinear regression, and time series analysis. Topics include the Gaussian platform, which is useful in analyzing computer simulation experiments. The book also covers the Response Screening platform, which is useful in testing the effect of a predictor when you have many responses.

Using JMP 11 shows you how to perform common tasks such as importing data, setting column properties, exporting analyses as graphics or HTML, and modifying JMP preferences. Details about connecting to SAS and working in the Formula Editor are also provided.

Provides conceptual information about the SAS programming language, as well as step-by-step examples that illustrate the concepts.

This book covers the basics of how to explore data and build reports using SAS Visual Analytics. The emphasis is on introductory instructions, how-to hints, and quick reference information.

In JMP, you choose from a wide repertoire of interactive graphs to help your data best tell its story. Delve into JMP 10 Basic Analysis and Graphing to find the ideal graph for your data, from basic distributions, bubble plots, scatterplots, and parallel plots to geographic maps and tree maps.

Discovering JMP for JMP 10 provides a basic introduction to using JMP. For new users of JMP, this is a great place to start. This book also includes initial instructions on working with your data, visualizing your data, analyzing your data, and saving and sharing your work

The JMP 10 Design of Experiments Guide contains information about the JMP Design of Experiments (DOE) platform, including the JMP Custom Designer. This book covers a wide variety of designs including design evaluation, screening, response surface, full factorial, discrete choice, space-filling, non-linear, Taguchi, augmented, mixture designs, and more.

JMP 10 Modeling and Multivariate Methods begins by showing you how to take advantage of classic modeling techniques such as linear, nonlinear, and mixed models. The book continues with discussions on neural networking, time series analysis, multivariate techniques, and stepwise regression along with many other JMP modeling and multivariate methods. Examples guide you through each analysis, and statistical references and algorithms are included.