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Data Analysis with JMP Software

Data Analysis with JMP Software

A challenge in applied statistics courses is getting from concept to effective application. While most statistics software requires the user to memorize commands, or where techniques and graphics are located in menus, JMP® provides a smart interface that reinforces concepts and provides an intuitive framework for real-world data analysis.

JMP includes comprehensive capabilities for statistical and graphical analysis of data for every academic field and most research needs. Easily perform basic statistics to the most complex analyses a PhD student may encounter. JMP runs on Windows and Macintosh operating systems and also functions as an easy, point-and-click interface to SAS®, R, MATLAB and Excel.

JMP is visual and interactive. It drives you through the statistical analysis workflow using point, click, drag and drop. And then it displays results as statistics and multiple graphs in the same window. In addition to the diverse set of tools JMP provides for analysis, you can easily subset, join and manipulate data tables in numerous ways, build summary tables using drag-and-drop and create 3D and moving graphics to help understand and communicate the results of your analyses.

General Agenda:

  • Navigating JMP and using its smart, graphical interface. 
  • Data visualization, including mapping, Graph Builder, data filters. 
  • Analyzing data in JMP: basic inference, ANOVA, regression, and multivariate analysis. Text Explorer.
  • JMP integration with SAS, MATLAB, R and Excel.
  • Other topics of interest (upon request), including design of experiments (DOE), quality, reliability/survival, data mining/predictive modeling, mixed models, repeated measures, bootstrapping, scripting, and time series.
  • New features in JMP 13 and JMP Pro 13:
    • New consumer research tools.
    • Local query builder and Excel import wizard.
    • Additional covariance structures for mixed models and repeated measures.
    • New generalized (penalized) regression models.
    • Deploying code to Python, C++, Javascript
    • Robust methods; missing data handling.
    • Instant output for interactive HTML reports and Dashboards.
  • Overview of available JMP academic resources.
Date:
Friday, February 10, 2017
Time:
10:00am - 11:30am
Location:
Bostock 127 (The Edge Workshop Room)
Campus:
West Campus
Categories:
Data and Visualization   Events @ the Edge  
Registration has closed.

Event Organizer

Profile photo of Angela Zoss
Angela Zoss