Reading Working Papers in Linguistics 4 (2000) - The University of ...

J. MARSHALL
which comes nearest to touching all of them. The measure of regression is
then based on how much distance there is between the regression line and the
actual points on the graph.
Correlations are shown in the following manner: a perfect negative
correlation will show as minus 1, and a perfect positive correlation as plus 1.
Scores close to zero will show no significant correlation. The reader will bear
in mind that these correlation tests are only first measures. The first batch of
Pearson’s Correlations reveal the following:
phovar ssscor lexrec lifmod socnet soclas attdia natpri
age 0.734 0.659 0.764 0.558 0.186 -0.432 0.334 -0.083
Those that correlate significantly are in bold. These correlation coefficients
show that:
AGE is correlated positively with 1) PHOVAR, 2) SSSCOR, 3) LEXREC, 4)
LIFMOD, and negatively with 5) SOCLAS. The correlation between age and
the linguistic scores comes as no surprise: the dialect is being lost, and
younger speakers do not have access to the range of dialect features that the
older ones do. As age is highly correlated with many variables, and as it is not
included in the hypothesis, its effects will have to be removed during the
model-building process in the regression analysis. Age also correlates highly
with LIFMOD. This shows that older people are less mentally urbanised than
younger ones generally. The effect of age has been smoothed out during the
model-building phase, so that correlations between LIFMOD alone and the
linguistic scores could be more rigorously tested. Age correlates negatively
with social class. This shows that younger folk are not only more educated,
but also read more national newspapers, and aspire to greater things
vocationally, for example.
Next the correlations between LIFMOD and the other variables were
considered:
phovar ssscor lexrec age socnet soclas attdia natpri
lifmo 0.782 0.767 0.704 0.558 0.186 -0.553 0.468 0.242
From this we can see that LIFMOD is positively correlated with PHOVAR,
SSSCOR, LEXREC, AGE, and ATTDIA, and negatively with SOCLAS. This
seems to show that, at this stage of the analysis at least, LIFMOD is a strong
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