About Us
Research Projects
Research Staff
Career Opportunities
Contact Us
Employee Advisories
Course Materials -- Statistics 210
A review of the statistical principles of data analysis using computerized statistical analysis procedures provided by the Statistical Statistical Analysis System (SAS). Statistical methods reviewed and applied include graphical displays (density estimation), univariate analyses, multiple regression, collinearity diagnostics, influence diagnostics, data-dependent model biases, analysis of contingency tables and categorical data, logistic regression for qualitative responses, analysis of variance and covariance, and the general linear model. Each week a statistical method is reviewed and sample analyses presented in SAS listings. Each week a data analysis project is assigned requesting that specific statistical analyses be performed and that the results be presented and interpreted in a typed statistical report. Each student is also required to complete an independent data analysis project. Prerequisites: 1) Stat 118, and 2) either Stat 157 or 201, and 3) Stat 183 or equivalent or proficiency with SAS.

Course Materials, 2003Programs and dataLecture 1 Listings
Lecture 2 Listings

Below are two sas programs and corresponding sets of log and listing outputs, one for "st210a_d.sas" the other for "st210a_u.sas". The latter uses the qqplot.sas macro that is included in the section below. The sas files are simple text files. There is a log and a lst file for each. Two versions of each are provided. One is a text file with a name such as "sa_dlog txt" for st210a_d.log, the other is a pdf file with a name "sa_dlog pdf". If you have adobe I recommend that you open and print the pdf file, especially the lst file. Otherwise you can open the txt files and try to print. You may have to highlight the document and change the font size to get it to print properly. Use print preview before actually printing.
Lecture 3 Listings
Lecture 4 Listings

Below is the sas file, saslog and listing files for the lecture 4. The pdf version of the listing file (a_r4lst.pdf)is about 85 pages with page breaks and is nicely formatted. The text version(a_rlst.txt) is shorter but is one continuous stream with no page breaks. The txt file can be reduced further by opening in ms word or word pad, hitting ctl-a to highlight all and then change the font to a smaller size.

If you use the txt file, be sure to use the print preview before printing to makesure that each line of output is not split between two lines (check the first line of each page, the page number should be on the far right). If the lines are split you should either use smaller margins or a smaller font size.
Lecture 5 Listings

Below are the sas files, saslog and listing files for lecture 5. There are two sets of files.

The current versions of these files were uploaded on 2/23/04 the day of the lecture. They include a new macro "resplot" that generates the variance plots within deciles of the predicted values. The sas code used previously had errors.

Because the file names are the same as before, your browser may have cached the old files when you click on the file name. After clicking on the file, when it opens, be sure to click the reload button to load the most current version of the file.

If you already downloaded these listings, the only thing that is different are the table of decile means and variances, and the corresponding plots.

A_R5 is a continuation of the A_R4 listing that was placed on the website for lecture 4.A_M is a new listing for a multiple regression analysis. this will be used in lecture 5 and lecture 6
Lecture 6 Listings

The following is an unpublished manuscript on identifying synnergism and antagonism in regression models. Please bring the tables to class since I will use them at the beginning of lecture 6. You can read the paper later if you wish.A_c is a new listing for a use of dummy variables for a categorical variable in a regression model
Lecture 7 Listings

The following listings for A_I.sas will be used in lecture 7 to describe collinearity and influence diagnostics for a regression model.
Lecture 8 Listings

The following listings for stat21B.sas will be used in lecture 8 to describe stepwise regression and cross validation.The following listings for sH_a.sas will be used to provide an introduction to logistic regression models.
Lecture 9 Listings

The following listings describe value added plots in logistic regression, stepwise models and cross validation.The following listings describe binomial regression and interaction models.
Lecture 10 Listings

The following listings describe analysis of variance.
Lecture 11 Listings

The following listings describe value unbalanced analysis of means (unbalanced ANOVA)Here is exercise 9 and the sas file. You will have to change the data set path before running the sas program.
Lecture 12 Listings

The following listings describe analysis of co-variance. The pdf file is 54 pages long and took 10 minutes to upload. The txt file can be downloaded much quicker.
Lecture 14 Listings

The following listings describe analyses of repeated measures. The pdf file is very long and took 10 minutes to upload. The lst file (not an ordinarytext file) can be downloaded much quicker. These files were generated using the BSC mainframe computer and thus may appear differently from other files generated using PC sas. For the lst file you should download and then open using wordpad or word.
Programs and data