SCS Short Courses, Winter 2000

SCS Courses Data Analysis Using SAS Introduction to SPSS for Windows Data Screening Applied Statistics with S-Plus

Data Analysis Using SAS

Basic introduction: Sessions One and Two provide an overview of SAS and its underlying logic, an explanation of the use of the Display Manager System to run a SAS job, an introduction to the SAS Data Step for reading, transforming, and storing data, and a demonstration of how statistical analyses may be performed in SAS Insight.

Further topics: Sessions Three and Four will concentrate on SAS programming techniques to modify data and enhance SAS output. More statistical procedures will be introduced for general linear models.

Introduction to SPSS for Windows

This course presents the basics of the Statistical Package for the Social Sciences (SPSS) including an introduction to computing concepts and the essentials of SPSS. Other sessions will demonstrate various ways of formatting data and will cover data modifications, transformations and the use of SPSS system files.

Session One will introduce the computing concepts of SPSS, the different facilities for reading data into an SPSS spreadsheet, and saving SPSS data files for future use. At the end of the first session, participants should be able to run simple programs, including some statistical procedures.

Sessions Two and Three will cover basic data modifications, transformations and other functions available in SPSS. More statistical procedures will be introduced, with an emphasis on the use of graphical methods to examine univariate and bivariate relationships.

Session Four will cover Analysis of Variance and Least Squares Regression. Graphical techniques will be demonstrated.

The following zip file: f99spss.zip (Last updated Fri Oct 1 1999) contains SPSS data sets and scripts used in the course. Copy this file (in binary mode) to an appropriate directory and use a zip extractor (such as pkunzip or WinZip) to expand the zip archive into the original files.

Data Screening

Data screening is the condom of data analysis: an important, but frequently overlooked step. While data analysis often focuses on summarization, model fitting, and numbers, data screening emphasizes exposure, preparation for modeling, checking the adequacy of assumptions, and graphical display. Come learn about Safe Stats!

This workshop covers a variety of practical aspects of data screening, including:

• Entering and checking raw data
• Assessing univariate problems (distribution shape, outliers)
• Assessing multivariate problems (multivariate normality, detecting multivariate outliers)
• Dealing with missing data Examples are presented using SAS software, along with a collection of general-purpose SAS macros for applying some of these techniques to any data set.

Applied Statistics with S-Plus

This course will explore a range of modern statistical methods implemented in S-Plus. It will start with a review of traditional linear regression and diagnostics to lead to robust and resistant regression, bootstrapping, generalized linear models for categorical dependent variables (including logistic regression), non-linear models, non-parametric regression, generalized additive models, tree-based methods, graphical methods in multivariate analysis, cluster analysis and time series analysis. Each method will be briefly discussed and we will look at a few examples of its use.

The course is based on "Modern Applied Statistics with S-Plus, 3rd ed." by W. N. Venables and B. D. Ripley, Springer, 1999.

SCS home page