Visualization and Imputation of Non-normal Missing Data: Short Course with Software
2014-09-16 16:58:36 GMT
Discounted 4-session live online course instructing on the use of 4 different data imputation techniques suitable for data that is not multivariate normal, for example, with PLS path modeling.
You receive complete training on the professional VIMGUI software, as well as unrestricted, permanent use of the software itself. VIMGUI supports the following contemporary data imputation techniques: (1) Hot Deck imputation; (2) k-nearest neighbor; (3) individual, regression-based imputation; and (4) iterative, model-based, stepwise regression imputation (irmi algorithm).
Course registration includes R-Courseware community user account through December of 2014. VIMGUI also provides extensive missing data visualization capabilities so you can see the 'missingness' data patterns to choose the most appropriate imputation approach.
If you want to learn how to perform statistical analyses; data analyses and/or data mining; graphical presentations of data; and/or programming with open-source R software for your school work or for your job, please consider this opportunity.
Included R-Courseware user account has 1300+ analytics, statistical, and data mining video and materials files on "hands on" research methods techniques.
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