Russel-Research-Method-in-Anthropology

Bivariate Analysis: Testing Relations 637
his or her social network; but (3) The linear regression equation is hardly any
better than the global mean at reducing error in predicting the dependent variable.
You can see this by comparing the mean line and the regression line (the
slightly diagonal line in figure 20.8). They are very similar.
What that regression line depicts, of course, is the correlation between age
and size of network, which is a puny –.099. But if we inspect the data visually,
we find that there are a couple of natural ‘‘breaks.’’ It looks like there’s a break
in the late 20s, and another somewhere in the 60s. We’ll break these data into
three age chunks from 12 to 26, 27 to 61, and 64 to 89, take separate means
for each chunk, and see what happens. I have marked the three chunks and
their separate means on table 20.19.
Like r, eta must be squared to find the variance accounted for. Eta 2 is calculated
from the following formula:
2 1
yy c 2
2
Formula 20.24
yy
where y c is the average for each chunk and y is the overall average for your
dependent variable. For table 20.19, eta-squared is:
2 1 3,871.55
10,058.55 .62
which is the proportionate reduction of error in predicting the number of
friends people have from the three separate averages of their age, rather than
from the global average of their age. This shows a pretty strong relation
between the two variables, despite the very weak Pearson’s r.
Statistical Significance, the Shotgun Approach, and Other Issues
To finish this chapter, I want to deal with four thorny issues in social science
data analysis: (1) measurement and statistical assumptions, (2) eliminating the
outliers, (3) significance tests, and (4) the shotgun method of analysis.
Measurement and Statistical Assumptions
By now you are comfortable with the idea of nominal-, ordinal-, and interval-level
measurement. This seminal notion was introduced into social science
in a classic article by S. S. Stevens in 1946. Stevens said that statistics like t