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LISA Statistics Short Course: Classification and Regression Trees (CART)
(Academic)
LISA SHORT COURSES IN STATISTICS
LISA (Virginia Tech's Laboratory for Interdisciplinary Statistical Analysis) is providing a series of evening short courses to help graduate students use statistics in their research. The focus of these two-hour courses is on teaching practical statistical techniques for analyzing or collecting data. See www.lisa.stat.vt.edu/?q=short_courses for instructions on how to REGISTER and to learn more.
Spring 2013 Schedule:
January 29: Designing Experiments and Collecting Useful Data*;
February 5: A Tutorial in T-Tests and ANOVA in JMP*;
February 12: Regression Analysis Using JMP*;
February 18: Introduction to R, Part I;
February 19: Introduction to R, Part I;
February 25: Introduction to R, Part II;
February 26: Introduction to R, Part III;
March 5: How to make plots to tell the story of your data;
March 18: Data Mining Basics;
March 19: Data Mining Basics;
March 26: Classification and Regression Trees (CART);
*These courses will be held in the GLC Room G, all other courses are in 3060 Torgersen Hall.
Tuesday, March 26; 4:00-6:00 pm;
Instructor: Dr. Chris Franck;
Title: Classification and Regression Trees (CART);
Course Information:
Classification and regression tree (CART) methods are a class of data mining techniques which constitute an alternative approach to classical regression. CART methods are frequently used in applications where it is difficult to specify an appropriate regression model explicitly. In this short course we will provide an overview of CART methods, apply these approaches to gain practical insight from data, demonstrate techniques to visualize predictions in the CART framework, and compare and contrast these methods with regression and other approaches. The goal is for students in this class to learn why, when, and how to use CART in their research. Students should have basic understanding of statistical principals and regression for this course. We will the R statistical programming package.
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More information...
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540-231-8354