
SCS CoursesData Analysis Using SASIntroduction to SPSS for Windows Data Screening Introduction to Structural Equation Modeling 
Instructor:  Gigi Luk, MA 

Dates:  Wednesdays, October 6, 13, 20 and 27, 2004 
Time:  9:30 a.m.  12:30 p.m. 
Location:  Steacie Instructional Lab, Room 021, Steacie Science Library 
Enrolment Limit:  30 
This short course provides a basic introduction to the Statistical Analysis System (SAS). 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.
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.
Instructor:  Lisa Fiksenbaum, MA 

Dates:  Tuesdays, October 5, 12, 19, 26, 2004 
Time:  12:30  4:00 p.m. 
Location:  Steacie Instructional Lab, Room 021, Steacie Science Library 
Enrolment Limit:  30 
This course presents the basics of the Statistical Package for the Social Sciences (SPSS). 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 including the uses of SPSS system files. More statistical procedures will also be introduced, with an emphasis on the use of graphical methods for examining univariate and bivariate relationships. Session Four will cover Analysis of Variance and Least Squares Regression. As with previous sessions, graphical techniques will be demonstrated.
Instructor:  Professor Michael Friendly 
Dates:  Wednesdays, Oct. 6, 13, 20, 2004 
Time:  1:00 p.m.  4:00 p.m. 
Location:  Room 030, Health, Nursing and Environmental Studies (HNES) Building 
Enrolment Limit:  30 
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:
Examples are presented using SAS software, along with a collection of generalpurpose SAS macros for applying some of these techniques to any data set.
 Entering and checking raw data
 Assessing univariate problems (distribution shape, outliers)
 Assessing bivariate problems (linearity, regression diagnostics)
 Assessing multivariate problems (multivariate normality, detecting multivariate outliers)
 Dealing with missing data
Instructor:  Professor Robert Cribbie 

Dates:  Wednesdays, Oct. 27, Nov. 3, 10, 17, 2004 
Time:  1:00  3:30 p.m. 
Location:  Lecture: Room 061 BSB 1:00  2:30 p.m.; Lab: Room 159 BSB (Hebb Computer Lab) 2:30  3:30 p.m. 
Enrolment Limit: 20 
This course will provide a general introduction to the methods of structural equation modeling (SEM), including a discussion of developing models, evaluating the fit of models to data, evaluating the significance of model parameters and performing model modification. The primary objectives of this class will be to provide:
 the ability to recognize situations where these techniques may be useful in research;
 an appreciation for the roles of sound theory in making these techniques useful;
 an understanding of the limitations of these methods; and
 the ability to use available software for analyzing data.