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SOCI209 - DESCRIPTION OF MIDTERM
The midterm for SOCI 209 has 42 multiple-choice
questions.
The main difficulty in anticipating, and
studying for, such an exam is psychological: human beings do not have built-in
internal gauges of the extent of their knowledge on any topic. So
when one introspects and tries to assess how much one knows, the internal
image is often a blank: it feels as if one knows nothing. This, however,
is an entirely spurious impression. Anyone who has been taking this
course so far knows a lot about regression models. The following
is a sample of the kind of knowledge on which the multiple-choice questions
in the midterm will bear.
meaning of the terms dependent and independent
variable
meaning of the error term epsilon
what are the parameters of a regression
model? (This is a bit tricky because the variance of e,
s2,
is also considered a parameter, in addition to the bk.)
what does the notation X ~N(m,
s2)
mean?
in what sense is the OLS estimator "least squares"?
what does BLUE mean?
knowing the estimated regression function and
the values of X and Y, calculate the residual
what does SSE measure?
what does MSE estimate?
know how to recognize a sum of squares when you
see its formula
what are the ranges of possible values for the
coefficient of correlation, for the r-square?
what patterns of the residual plot suggest non-independence
of the errors, heteroskedasticity, etc.?
what patterns of the residual plot suggest that
errors conform to the assumptions of the regression model?
know what tests or procedures can be used to
identify outliers or diagnose a pathological condition such as heteroskedasticity
or non-normality of residuals
given a matrix expression, determine the dimension
of the result; there are 5 questions of this type, involving matrix expressions
used in the regression model
what is the substantive interpretation of a regression
coefficient?
in a multiple regression model, what df are associated
with regression, error, and total?
calculate the R-square in terms of sums of squares
know the general properties of R2
and of Ra2
in a multiple regression model, knowing regression
coefficient and s.e., test the coefficient for significance at the .01,
.05 or .10; the necessary statistical calculations are provided in an Appendix
to the exam, in SYSTAT and STATA language
know how to conduct an F test of the existence
of a regression relation between Y and the independent variables
interpret the coefficient of an indicator variable
now what the coefficient of multiple correlation
is, and what values it can assume
how many indicators are needed to represent a
nominal (categorical) variable with k categories?
knowing the regression estimates, calculate the
response function for a specific category of a nominal variable
understand the meanings and properties of a polynomial
regression, and of a regression model with a interaction term
interpret the coefficient of an interaction term
involving an indicator variable