COM 508 Quantitative Foundations of Communication
PSC 508 Basic Statistics for the Social Sciences
Fall Semester 1999

Instructor: Dr. Frank Tutzauer (

This course is designed to introduce the Social Sciences graduate student to the quantitative analysis of data. Although a familiarity with computers and with certain mathematical and statistical ideas will be helpful, none is assumed.

We will begin with certain mathematical fundamentals. Then we will move to a discussion of data and variables, followed by computers and SPSS, probability, and descriptive and inferential statistics. Throughout, we will see how various data-analytical problems can be solved using SPSS. A course outline is presented below, but it is tentative. We may add or delete topics as time allows or requires.

Grading will be based on two exams and a variety of take-home and lab assignments. The assignments, taken collectively, will be worth a third of the grade, as will each of the exams. Plagiarism, defined as repeating the words or ideas of another as though they were your own, and all other forms of academic dishonesty are expressly prohibited and will be punished with the severest penalties possible.


Tentative Course Schedule:

Week Topic Readings
DONE Mathematical Fundamentals  
DONE     Sets and numbers  
DONE    Functions  
DONE  Descriptive Statistics WW ch 1-2
DONE    Variables (informal)  
DONE   Populations and samples  
DONE    Levels of measurement  
DONE    Histograms and cross-tabulations  
DONE    Measures of central tendency  
DONE    Measures of dispersion  
DONE    Intro to SPSS  
DONE Probability WW ch 3
DONE    Basic notions  
SKIPPED    Conditional probability  
DONE    Random variables  
DONE    Probability distributions  
DONE  Inferential statistics WW ch 4, 9
DONE    Binomial distributions  
DONE    Tests of proportions  
DONE    Type I and type II error  
DONE    Normal distributions  
DONE    Central limit theorem WW ch 6, 8
DONE    z- and t-tests  
DONE    Confidence intervals  
    Analysis of variance (ANOVA) WW ch 10
    Scatterplots, covariance, and correlation  
    Regression WW ch 11-13, 15
    Cross-tabulation and log-linear analysis WW ch 17

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