Welcome to Psychology 830!
Recitation: Friday 3:00-3:50 in Dey 206
Office Hours: Mondays 10:00-11:30 & Wednesdays 1:00-2:00,  in Davie 339
My E-mail Address: dserrano@email.unc.edu

The lab serves as a complement to the lecture.  We will mainly deal with computing related issues and your homework problems during lab sessions, although if you have questions about material presented in the lecture please feel free to ask me.  Each week in recitation I will demonstrate how to perform data analysis in each of these programs.  The code for these techniques will be posted on this page (hopefully, by Thursday night so you can print it out for class), along with useful explanations about the code.

As to the computing required in this class, we recommend these three programs: SAS, SPSS, and R.  You may use any one of these programs to complete your homework assignment.  Note that you may not have to type in the data for your assignment, the dataset comes with the CD in the back of the textbook.  Come see me if the book you bought does not have the CD in it.

  • UNC students: SAS and SPSS are available in the computer labs in Davie Hall; talk to Hugh Merriwether or Walt Bowen in Davie 359 if you would like to load it on your own computer.  SAS is also available through ATN software acquisition for free (you have to trade them several blank CDRs for the SAS disks).  You can also obtain SPSS from software acquisition, and it costs about $30 initially, and it requires annual license renewal ($20).  R is an open-source implementation of the S language that can be downloaded for free from this site

 

Spector, Paul E. (2001). SAS Programming for Researchers and Social Scientists.
Delwiche, Lora D. (1998). The Little SAS Book.
DiIorio, Frank C. (1991). SAS Applications Programming: A Gentle Introduction.
Hatcher, Larry and Stepanski, Edward J. (1994). A Step-by-Step Approach to Using the SAS System for Univariate and Multivariate Statistics.
Cody, Ronald P. & Smith, Jeffrey K. (1997). Applied Statistics and the SAS Programming Language. 4th Ed.

Date

Schedule

08-25-06

Introduction to programs

09-01/08-06

Looking at Data: Descriptive Statistics and Plots

 

09-15-06

Bivariate Relationships

 

09-22-06

Fun with R and a look into the future with SAS

 

09-29-06

Probability, Sampling, and the Central Limit Theorem (CLT)

 

10-06-06

 

10-13-06

 

10-20-06

 

10-27-06

Entering data and T-Tests

 

11-10-06

Regression, ANOVA, and the General Linear Model

 

11-17-06

ANOVA, and the General Linear Model: Coding Schemes, Contrasts, and Standard Error Computation

 

11-24-06

 

12-01-06

 

12-08-06

 

12-15-06