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JSL Workshop

A popular format for increasing knowledge and proficiency in the use of the JMP scripting language.  The workshop has a large element of hands-on activities supported by extensive code examples.


Be Inspired!

Success with JSL requires not only a technical understanding of the scripting language but also imagination and understanding in the ways that it can be applied to help your data analysis workflow.  To help inspire you the workshop will showcase real-life case studies illustrating the power and scope of JMP scripts, including Gage R&R studies, capability analysis, data-import wizards, models diagnostics and custom dashboards.



You produce the same output every week.  Discover how to automate and customise the creation of these reports.


Data handling

It is estimated that 60%-70% of data analysis is consumed by data handling activities.  JMP scripts can be used to streamline access to data giving you more productive time to get insights from your data.  On this workshop you will be provided with a framework called "DIPP" - data input and pre and post processing. To work with the framework you will learn about functions, string manipulation and pattern matching.  The framework will allow you to import data from text files, perform data manipulation prior to the creation of a JMP table, and finally to automatically attach analysis scripts to the table.  With an understanding of the JSL building blocks the framework can easily be extended to handle data from data collection devices, spreadsheets and databases.


Navigation Wizard

A wizard is a user-interface style that navigates you through a sequence of steps using next and back buttons.  Alternatively, the buttons can be used to scroll through a sequence of JMP output reports.  We'll look at a framework for developing an easy-to-use navigation system using the JMP scripting language.


Iterative Analytics

Why settle for one model when you can investigate hundreds!  Scripts make it possible to explore the properties and behaviours of models and to develop insights into how these models perform in relation to their initial specifications.  This technique is particularly applicable to advanced models such as decision trees and neural networks where there are many parameters that can be used to specify the initial forms of the models.  In the workshop you will discover how to automatically run multiple models and extract summary statistics to describe their performance.  These techniques apply not only to models but to all forms of repetitive statistical analysis.



1 day

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