Description – Topics include: Entering data, descriptive statistics, graphing data, cross tabulations, t-tests, correlation and regression, and analysis of variance.
 

Pre-requisite– Statistics course. Graduate students and/or Advanced undergraduates.
 

Objective– The objective of this lab course is to teach the fundamentals of SAS for Windows in analyzing data for research
 

Room: PC 419  Five Fridays 9:30-12:15 January 14, 21,28, February 4,11, extra class February18.
 

SAS for Windows Lab – Syllabus (5 double classes in lab).
 
 

Class                     Possible Topics

1          Introduction to SAS and Enterprise Guide. Icons, Opening files, File extensions. Different methods of accessing SAS. Procedures: Freq, Means.
 

2         Entering data from different sources. Coding and labeling variables. Computing new variables in data step. Procedures: Freq for crosstabulations.
 

3        Hypothesis testing. Procedures: means, ttest for one sample, independent samples and paired samples t-tests.
 

4        Procedures: Scatterplots, Correlation, Regression. Saving data from a procedure (residuals).
 

5        One and two-way ANOVA using GLM.
 
 

Justification for 1-credit SAS Data Analysis in Research course.
 

There is no hands-on laboratory course focusing on SAS for Windows at the University even though FIU has a SAS for Windows license so it is available for students for price of cds. It is also available in student labs on all campuses. This course will assist graduate students on using SAS for analysis of their thesis data.

Currently, SAS is used in various research methods courses in the University– Statistics, Biology, and Business. However, these courses generally expect the students to learn SAS on their own. For the graduate students readying themselves to enter and manipulate their own thesis data , there is no assistance in the details of using SAS. And even though these students have learned many statistical procedures in their courses, they need guidance in setting up the appropriate tests in the statistical package to be able to answer their research questions and hypotheses. Thus there is a need for a course covering: how to enter data (coding, transformations, recoding, transferring data from other programs such as Excel, and labeling variables so the output is readable, functions), how to perform statistical techniques (test variables, factors, independent variables, what options are necessary, how to locate help, etc.), and how to manipulate output (tables, graphs, exporting both). With these skills, graduate students will be able to perform their data analysis faster and more efficiently.
 

CONFIRMED Textbook.

Step-by-Step Basis Statistics Using SAS: Student Guide, by Larry Hatcher.  ISBN 1-59047-148-2 BBU Press, April 2003.  Buy from SAS $69.95

http://www.sas.com/apps/pubscat/bookdetails.jsp?catid=1&pc=57321

There is an exercise book but it is not required.