Resource Center
Basic Data Analysis and Modeling
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Analyzing Curve Data with JMPIn this webinar, you’ll learn how tools in JMP will help you better understand the variation in the shape of curves and how to use curves in Design of Experiments and modeling to better understand how input variables effect the shape of curves.
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Decoding Python: Shorten the time from discovery to model deployment using JMP ProIn this webinar, you’ll learn more about JMP Pro, a powerful data analysis software tool that provides an intuitive and user-friendly interface for data visualization, modeling, and analysis, and how it integrates with Python.
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Data Visualization and Model BuildingIn this paper, Richard De Veaux, Williams College, explains how visualization and data exploration can be used to draw conclusions about sports performance as we age.
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Accelerating Your Analytic WorkflowThis three-session webinar series provides practical tips, tricks and best practices to effectively prepare and analyze your data, and then share your data discoveries.
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Regression and Analysis of VarianceIn this chapter excerpt from Peter Goos and Ellen Vandervieren's book Regression and Analysis of Variance, you'll learn about the use of multiple quantitative explanatory variables in JMP.
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The Top 7 Myths That Lead to Really Bad GraphsIn this brief, we review seven of the most common misconceptions when visualizing data. When these myths are dispelled, your charts will be more effective and easier to design.
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Session 4: Basic Analysis and ModelingDuring this session, Jordan Hiller demonstrates simple techniques for building models and the enriching insight gained from those models.
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XaarSix Sigma champions accelerate an analytics transformation.
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Producing and Interpreting Basic Statistics Using JMP® JMP lets you interactively produce analyses, graphs and associated statistics at the same time. See how to generate and interpret basic summary statistics, fit distributions and perform hypothesis testing on the mean and on the standard deviation.
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Basic Analysis and PlottingSee, in this case study about housing prices in three cities, how to visualize data to make analyses accessible to statisticians and non-statisticians.