JMP 13 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 13 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.

JMP 13 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.

Using JMP 13 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 a point of entry for understanding the basics of the SAS Intelligence Platform. It discusses the benefits of the SAS Intelligence Platform to businesses, describes the architecture, and provides an overview of each software component. This document can be used alone or as an introduction to the deployment and administration guides.

Describes the basics of using the SQL procedure and provides comprehensive reference information. The usage information includes retrieving data from single and multiple tables; selecting specific data from tables; subsetting, ordering, and summarizing data; updating tables; combining tables to create new tables and useful reports; performing queries on database management system (DBMS) tables; using PROC SQL with the SAS macro facility; and debugging and optimizing PROC SQL code. The reference information includes statements, dictionary components, and system options.

Contains the complete reference for all Base SAS procedures. Provides information about what each procedure does and, if relevant, the kind of output that it produces.

Contains the complete reference for all Base SAS procedures. Provides information about what each procedure does and, if relevant, the kind of output that it produces.

Explains how to increase the modularity, flexibility, and maintainability of your SAS code using the SAS macro facility. Provides complete information about macro language elements,

Describes the basics of using the SQL procedure and provides comprehensive reference information. The usage information includes retrieving data from single and multiple tables; selecting specific data from tables; subsetting, ordering, and summarizing data; updating tables; combining tables to create new tables and useful reports; performing queries on database management system (DBMS) tables; using PROC SQL with the SAS macro facility; and debugging and optimizing PROC SQL code. The reference information includes statements, dictionary components, and system options.

PIntroduces the core functionality of SAS Enterprise Miner and shows how to perform basic data mining tasks. Provides step-by-step examples that create a complete process-flow diagram including graphic results.

Provides conceptual information for the Base SAS language. Major topics include SAS keywords and naming conventions, SAS variables and expressions, error processing and debugging, SAS data sets and files, creating and customizing output, DATA step concepts and DATA step processing, reading raw data, and creating and managing SAS libraries.

Provides usage information and examples for Output Delivery System (ODS) capabilities. The document describes a wide range of formatting options and shows how to gain greater flexibility in generating, storing, and reproducing SAS procedure and DATA step output.

Using JMP Student Edition is the official user guide for JMP Student Edition, the streamlined edition of JMP for first year statistics students. Clearly written, with easy-to-follow, step-by-step instructions, this book provides engaging illustrations and concept overviews. Chapters cover JMP basics such as importing data, creating formulas, creating graphs with Graph Builder, and performing univariate and bivariate data analysis. More complex analyses are covered, including Partition, Multiple Regression, Time Series, Design of Experiments, Variability Gauge Charts, and Quality Control, and more. JMP Student Edition software is available from major textbook publishers when packaged with their textbooks for course use.

Discovering JMP 12 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 12 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. Find information about how to clean up your data before performing analyses.

JMP 12 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.

JMP 12 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. Discover JMP’s definitive screening designs, an efficient way to identify important factor interactions using fewer runs than required by traditional designs. And read about creating designs that test systems where failures occur as a result of interactions among components or subsystems. The book also provides guidance on determining an appropriate sample size for your study.

Start with JMP 12 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 12 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 12 JSL Syntax Reference focuses on functions and their arguments, and messages that you send to objects and display boxes. Notes and examples are included.

JMP 12 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, principal components, discriminant analysis, and partial least squares.

JMP 12 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 12 Quality and Process Methodsfocuses 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.

JMP 12 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.