Statcon. Statistik: Consulting · Training · Software

This one-day course contains an introduction to JMP, its philosophy and extensive capabilities for graphical data analysis. You will learn to perform an exploratory data analysis and explore patterns of data.
We discuss navigating the JMP interface as well as methods for data management (importing and exporting data) and presentation of results. In the framework of exploratory data analysis you
will learn to use decision trees and to perform and interpret descriptive statistics.

Objectives:

• Import data and open different types of data files
• navigate the JMP interface
• use the columns and rows menus in an efficient way
• create new tables with statistical parameters
• generate decision trees
• export results and create reports

Prerequisities:

None.

In this course we introduce the two most important methods of data analysis: analysis of variance (ANOVA) and regression. We start with basics of descriptive statististics, explorative data analysis and
statistical testing. Then we turn the focus on comparing means. Beginning with t-tests you will learn to perform one-way and two-way ANOVA models. The second focus of this course is on regression.
We discuss simple linear regression, non-linear regression as well as multiple regression and regression diagnostics. After this training you will be able to analyse data with one continuuous response variable.

Objectives:

• Apply methods from explorative data analysis
• Formulate and understand statistical hypothesis
• Perform simple, paired and two-sample t-tests
• Perform and analyse one-way and N-way ANOVA models
• Fit and analyse simple and multiple regression models and examine assumptions

Prerequisites:

We do not introduce the basic use of JMP in this course.
Before attending the course, you should complete the data exploration course (JDEX) course or have equivalent experience.

One of the principles of the Design of Experiments (DoE) methodology is to create efficient experiments, i.e. gain information from a small number experimental runs.
This course focuses on basic methods of designing and analyzing experiments. We start with full and fractional factorial designs in order to identify the few important factors (screening designs).
Then we turn our attention to response surface designs leading to optimal factor settings with respect to different types of optimization criteria. This training covers classic approaches of DoE as well as modern, user-defined methods (Custom designs).

Objectives:

• explain the fundamental principles of designed experiments
• understand and use blocking and randomization of designs
• create and analyze full and fractional factorial screening designs
• create screening designs to identify the important factors
• create and analyze response surface designs
• use the custom design tool in JMP in the right way

Prerequisites:

Before attending this course, it is recommended you complete the JMP Software: Data Exploration (JDEX) course or have equivalent experience. Experience in ANOVA and regression methods, e.g. based on the JANR training, is helpful.

This course focuses on using the JMP Scripting Language (JSL) to automate routine procedures, extend or create new procedures, and customize reports. The course is an introduction to JSL. It gives students the basic tools for extending JMP functionality to their own business or research questions.

Objectives:

• Scripting Concepts
  • introducing scripting
  • introducing object-oriented approach
  • reviewing how to generate scripts interactively
  • storing scripts in the Table panel
• JSL Building Blocks
  • understanding operators, numbers, and names
  • understanding lists and expressions
  • understanding comments, commas, parentheses, quoted strings, and matrices
  • introducing a visual JSL style to make reading, interpreting, and understanding JSL easy
• Functions
  • using the For and For Each Row functions
  • using the If, Match, and Choose functions
• Data Table Scripts
  • creating new tables and columns
  • changing or adding column properties
• Platform Scripts
  • understanding platform layers (analysis and report)
  • reporting display tree structure
  • building custom windows
• Dialogs and Lists
  • making and using custom dialogs
  • listing data structures
  • understanding expressions and evaluation
  • journaling results
• Packaging Scripts
  • understanding generic arguments
  • using and understanding the User Toolbar and User Menu

Prerequisites:

Before attending this course, it is recommended you complete the JMP Software: Statistical Data Exploration course or have equivalent experience.