Sai Wang's guest appearances

Sai Wang

LISA: Laboratory for Interdisciplinary Statistical Analysis - Short Courses

ERIC SMITH

Matt Williams

Anne Ryan

Block Design

Qing Li

Eric Vance

Jonathan Stallings

Khaled Bedair

Yiming Peng

Mark Seiss

Chris Franck

Nels Johnson

Marcos Carzolio

Liang Shan

Wandi Huang

OwlTail

R is a free computing and graphical software/environment for statistical analysis. This short course consists of 3 sections:    Section 1 provides introduction to R programming basics, such as data objects in R, loops, import/export datasets, along with examples of data manipulation/cleaning.    Section 2 discusses the R graphing environment and how to create some basic statistical plots.    Section 3 introduces how to perform basic statistical analysis in R, such as t-tests, ANOVA and linear regression.Course files available here: www.lisa.stat.vt.edu/?q=node/2317.

R is a free computing and graphical software/environment for statistical analysis. This short course consists of 3 sections: Section 1 provides introduction to R programming basics, such as data objects in R, loops, import/export datasets, along with examples of data manipulation/cleaning. Section 2 discusses the R graphing environment and how to create some basic statistical plots. Section 3 introduces how to perform basic statistical analysis in R, such as t-tests, ANOVA and linear regression. Course files available here: <a href="http://www.lisa.stat.vt.edu/?q=node/2317" rel="nofollow" target="_blank">www.lisa.stat.vt.edu/?q=node/2317</a>.

Introduction to R by Sai Wang

R is a free computing and graphical software/environment for statistical analysis. This short course consists of 3 sections:Section 1 provides introduction to R programming basics, such as data objects in R, loops, import/export datasets, along with an example of data manipulation/cleaning.Section 2 discusses the R graphing environment and how to create some basic statistical plots.Section 3 introduces how to perform basic statistical analysis in R, such as t-test, ANOVA and linear regression.Course files available here: www.lisa.stat.vt.edu/?q=node/1947.

R is a free computing and graphical software/environment for statistical analysis. This short course consists of 3 sections: Section 1 provides introduction to R programming basics, such as data objects in R, loops, import/export datasets, along with an example of data manipulation/cleaning. Section 2 discusses the R graphing environment and how to create some basic statistical plots. Section 3 introduces how to perform basic statistical analysis in R, such as t-test, ANOVA and linear regression. Course files available here: <a href="http://www.lisa.stat.vt.edu/?q=node/1947" rel="nofollow" target="_blank">www.lisa.stat.vt.edu/?q=node/1947</a>.

Intro to R by Sai Wang

In many applications, the response variable is not Normally distributed. GLM can be used to analyze data from various non-Normal distributions. In this short course, we will introduce two most common GLM models: Logistic Regression for binary (yes/no or 0/1) data and Poisson Model for count data. Examples of fitting GLM models using JMP and interpretation of outputs are also provided.Course files available here: www.lisa.stat.vt.edu/?q=node/1177.

In many applications, the response variable is not Normally distributed. GLM can be used to analyze data from various non-Normal distributions. In this short course, we will introduce two most common GLM models: Logistic Regression for binary (yes/no or 0/1) data and Poisson Model for count data. Examples of fitting GLM models using JMP and interpretation of outputs are also provided. Course files available here: <a href="http://www.lisa.stat.vt.edu/?q=node/1177" rel="nofollow" target="_blank">www.lisa.stat.vt.edu/?q=node/1177</a>.