Expand Your Analytic Skills
Transforming Data to Make Better Predictions (Intermediate)
November 15, 2019 | 2 PM ET (11 AM PT)
One of the statistical assumptions for regression is that the error (variance) is distributed normally and uniformly across the range of the data. Although statisticians often transform data to a new scale (e.g. take the logarithm of the response) to make the error better match this criterion, engineers and scientists doing the same modeling might not be aware of this assumption. As a result, neglecting to transform the data when creating a model can yield physically impossible and potentially embarrassing results, such as negative values of hardness, resistivity, or the number of defects. JMP guides users to choose an appropriate transformation that will yield a logical and useful model.
This webinar covers: an overview of principles of data transformation, descriptions of situations where transformation is important, and several case studies using Fit Model and Box-Cox transformations.
Register now for this free, one-hour, interactive webinar.
Date: Friday, November 15, 2019
Time: 2 PM ET (11 AM PT)