

OCTOBER
12 
SPSS Guide, Ch.11: "Bivariate and Partial Correlations," only 177183. If your variables are continuous, or if you can treat them as points along a conceptual continuum, relationships can be measured and expressed precisely and concisely through the twin techniques of productmoment correlation and regression. Correlational analysis is one of the most common techniques in social research. In essence, it tells us in what direction two variables are related and how strongly they are related. 

OCTOBER
15 Also see 
SPSS Guide, Ch.11:
"Bivariate and Partial Correlations," only 183187.
Read about the Spearman Rank Correlation, but you need not
concentrate on this statistic. The section on "Partial
Correlations" is more important. The strength of association between two intervallevel variables is actually expressed by the coefficient of determination, which is simply the square of the product moment correlation. Field tests several hypotheses about the policies of different nations toward abortion, including one holding that Catholic countries would have more conservative abortion policies than nonCatholic ones. Are these hypotheses supported or refuted by her data analysis? Assignment: Formulate a hypothesis about the effect of socioeconomic characteristics on politics in American states and test it using data from the nustates2000 file. You must select a dependent variable (the political outcome you wish to explain) and an independent variable (the socioeconomic characteristic that is a likely explanation of the outcome).
Print the output for this analysis and bring it to class on Monday. I will give a valuable PRIZE to the student who turns up the highest meaningful correlation in support of his or her chosen hypothesis. Determine for yourself whether the hypothesis was supported by the data. Using the statistics generated from the sums of squares for the two variables and their crossproducts try to compute the correlation value, r, as explained in the lecture notes. Try to work this out on your own before I show how in class. A QUESTION LIKE THIS WILL BE ON THE 2/3 EXAM.


OCTOBER
16 
SPSS Guide, Ch.12:
"Simple and Multiple Linear Regression," only
189204. We visualized the value of the productmoment correlation, r, as indicating the degree to which the observations hugged "the best fitting straight line" without actually calculating that line. Regression analysis requires doing that. Whereas correlational analysis tells the strength of a relationship, regression analysis indicates the specific form of a relationship. Knowing the mathematical form of a relationship allows one to predict a value of a dependent variable (Y) with knowledge of an independent variable (X). A great deal of advanced statistical analysis is predicated on the ideas in simple linear regression. Learn this well.


OCTOBER 17 
Optional Session: Review for 1/3 examination Go here to view a "pretest"sample questions for the 1/3 exam. The discussion section will be based on this pretest, which illustrates the type of questions that will appear on the 1/3 exam. 

OCTOBER
18 
Marilyn J. Field, "Determinants of Abortion Policy in the Developed Nations," Policy Studies Journal, (Summer, 1979), 771781. (On website) Assignment: Earlier versions of SPSS contained a simple PLOT procedure that also produced regression statistics. SPSS 10 has dropped that simple procedure, but one can get a plot with regression statistics. This procedure is described by Ms. Wuyi Wang, a former TA in this class, who is now a technical consultant at SPSS, Inc. She writes:
A scatterplot made this way has the regression line and Rsquared. As you did when you formulated your hypothesis for Monday, choose a pair of variables that you'd like to correlate. But this time, follow Wuyi Wang's instructions. More instructions are given in the lecture notes for this day. 

OCTOBER 19 
1/3 EXAMINATION  it will consist of 30 questions, mostly calling for short answer or selection of multiple responses. It will also ask for some elementary computations that require your understanding of key formulae in statistics. 

OCTOBER 22 