Business Knowledge Series course

Presented by Heath Rushing, co-founder and Principal Consultant, Adsurgo LLC; or Jim Wisnowski, Ph.D., Adsurgo LLC

This course combines the use of JMP with basic, intermediate, and advanced analytical methods. Interactive illustrations enable course attendees to understand statistical concepts by engaging and experimenting with them. To help guide them, attendees are also provided a set of flowcharts that integrates JMP tools into a process that shows them where they are, where they are going, and when they have fully completed the analysis. This course provides specific advice on how to exploit these methods in the real world. Engineers, scientists, and other analysts attending the course will come out prepared to take on problems and reveal exploitable insights.

Learn how to effectively use JMP to

• Import and arrange data for analysis, including JMP data table productivity features.
• Handle data format challenges with a variety of JMP tools.
• Explore data, including unstructured text data.
• Create summaries, tables, charts, and graphs.
• Solve a variety of scientific and engineering problems from single to multiple factors and responses.
• Recognize and deal with statistical challenges.
• Describe and analyze the distribution of data.
• Describe the relationship between and among two or more factors or responses.
• Understand issues related to sampling, and calculate appropriate sample sizes.
• Generate and analyze statistical intervals and hypothesis tests to make data-driven decisions.
• Complete univariate, bivariate, and multivariate analyses using both continuous and categorical factor variables.
• Identify problems with analyses, such as violating statistical assumptions, and how to deal with them.
• Consolidate analyses into presentations.

Who should attend

Engineers, scientists, and technicians who intend to do product or process improvement

Formats available	Standard Duration
Classroom:	3 days
Live Web Classroom:	6 half-day session(s)	System Requirements

Before attending this course, you should have a general familiarity with computers. There are no prerequisites but familiarity with spreadsheet software is helpful.

This course addresses JMP software.

Introduction to JMP

• Navigating JMP.
• Importing data tables into JMP.
• The column menu.
• The row menu.
• Data table manipulation.
• Formulas.

Graphical Analysis

• Principles of graphical excellence.
• Univariate graphs.
• Bivariate and multivariate graphs.
• Time series and maps.
• Text exploration.

Descriptive Statistics

• Introduction to summary statistics.
• Describing a distribution of values.
• Summary tables and Tabulate.

Intervals

• Confidence intervals, prediction intervals, and tolerance intervals.

Hypothesis Testing

• Introduction.
• Means tests.
• Proportion tests.

ANOVA

• Analysis of variance.
• Definitions.
• Assumptions and interpretation.
• One-way ANOVA in JMP.
• Multiple comparisons.

Simple Linear Regression

• Scatterplots and correlation.
• Simple linear regression.

Model Building

• Introduction to model building.
• N-way ANOVA.
• Multiple linear regression.
• ANCOVA.

Model Diagnostics

• Evaluating the validity of the model assumptions.
• Evaluating model fit.

Categorical Response Analysis (Self-Study)

• Contingency analysis.
• Logistic regression.

Additional Topics (Self-Study)

• Components of a quality system.
• Measurement Systems Analysis (MSA).
• Design of experiments.
• Statistical process control (SPC) and capability.