SCS Short Courses, Fall 1999

SCS Courses Introduction to SPSS for Windows Data Analysis Using SAS Data Analysis and Statistical Graphics Using S Overview of Statistical Computing with Stata Mixed Models Using S-Plus and SAS

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.

Mixed Models Using S-Plus and SAS

A linear mixed effects model is an extension of ordinary linear regression that allows random as well as fixed regression coefficients. Mixed models can be used for many types of data that are otherwise difficult to analyze including longitudinal data, unbalanced repeated measures, multilevel data and unbalanced block designs. This course will present a review of linear models and an overview of the basic theory and applications of mixed models. The fitting of mixed models will be illustrated with a number of examples covering a range of applications. The NLME version 3.0 software of Douglas Bates and Jose Pinheiro will be used for its flexibility in visualizing data for mixed models. NLME is written in S-Plus. PROC MIXED and PROC NLMIXED in SAS will also be discussed.

Overview of Statistical Computing with Stata

This course is a brief introduction to Stata for experienced data analysts. Topics covered will include the user interface, data management and manipulation, linear m odels and graphics. Features of the Stata environment will be compared to some common alternatives. A variety of examples will be used to demonstrate features of the program.

Data Analysis and Statistical Graphics Using S

Many feel that S is the language of choice for the development of new statistical tools and for interactive analysis of data. A commercial version, S+, is available on Unix workstations and on PCs under Windows. At York, S+ has been installed on the "phoenix" Unix system, in the Hebb Lab in Psychology and in the Gauss Lab in Mathematics and Statistics.

The purpose of this course is to learn how to use S in a Unix or in a Windows environment. The course will have both lecture and hands-on components. Participants will have access to an account to run S+. The four sessions of the course will cover approximately the following material:

• I The Unix or Windows Environment. Unix: Logging in, editing with vi, directory structure, basic file manipulation, introduction to the X-Window environment. Microsoft Windows: The S-Plus graphical user interface. Overview of S.
• II Basic Use of S: Data input, manipulating data, printing, history mechanism, S arrays and data frames, random number generation, arithmetic operators; functions for manipulating data structures: apply and table; help facilities.
• III Programming and Graphics in S: Writing S functions, one-and two-dimensional graphs, interactive graphs, trellis graphics.
• IV Introduction to the use of statistical functions in S: Regression and regression diagnostics based on the linear model function, lm().
The main reference for the course will be "Modern Applied Statistics with S-PLUS, 3rd edition" by W. N. Venables and B. D. Ripley (Springer, 1999).

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