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LISA Statistics Short Course: T-tests and ANOVA
(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.
Fall 2013 Schedule:
Monday & Tuesday, September 23 & 24: Basics of R;*
Monday & Tuesday, September 30 & October 1: Statistical Analysis in R;*
Monday & Tuesday, October 7 & 8: Graphing in R;*
Thursday, October 17: Survey Design and Analysis;
Thursday, October 24: Design of Experiments;
Thursday, October 31: T-tests and ANOVA;
Monday & Tuesday, November 4 & 5: Introduction to JMP;*
Tuesday, November 12: Nonparametric methods featuring the bootstrap;
Thursday, November 21: Regression Methods;
*Two sessions of the same course to accommodate more attendees.
Thursday, October 31;
Instructor: William Tyler Bradley;
Title: T-tests and ANOVA;
Course Information:
The t-test and analysis of variance (ANOVA) are two of the most common statistical techniques used in practice. These techniques allow researchers to statistically assess the plausibility that a feature of a population differs from a hypothesized value on average, or that two or more samples or groups differ in terms of an outcome of interest. For example, comparing the height of grain under a specific fertilizer treatment to a specified value of interest or comparing the heights of several fertilizer treatments to each other. Inference is conducted at the population level on the basis of sample data.
This short course is designed to provide an overview of these approaches. Concepts and caveats underlying hypothesis testing will be reviewed. The t-test portion will include one-sample, two-sample, and paired tests. ANOVA can be used to compare more than two groups. This test and its variations (i.e. two-way ANOVA and ANCOVA) will be covered as well. Course coverage includes these methods' underlying assumptions, how to check for them, and procedures for some cases when the assumptions are not met. Datasets will be either simulated or built into R, such as the iris dataset. Code for this data, graphics, and the demonstration will be available. This course will focus on the mechanics and concepts underlying t-tests and ANOVA. Because of this, the course will be held in a lecture hall and not a computer lab. Implementation of these tests in JMP and R will be covered in other short courses.
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More information...
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540-231-8354