Explain this regression analysis IN DETAIL. Your explanation should
include:
a) the null and alternative hypotheses
b) the coefficients estimates (value and direction)
c) the significance of each independent variable using either the t
statistics or confidence intervals (or both for ex cr)
d) the overall goodness of fit of the model
Part IV Regression
(15 points)
Suppose you have data on members of the House of
Representatives including “tenure” which measures the number of
years each member has been in office, a measure of their voting record called “votescore” which ranges from –100 (liberal) to +100 (conservative), their party (Democrat =1, Republican =0), and their
race (0 = white, 1 = black, 2 = latino). You want to predict
members’ voting record using ALL available variables.
a) What is your DV and your IVs?
b) Write out the null and research hypotheses for each
independent variable in the model (be VERY precise in your
wording). You should use your common sense to make an
argument about what effect each factor might have on
members’ voting record.
c) Using ALL of the variables listed above, write down the
equation for the model that you would use to predict members’
voting record. If you were going to estimate this model with R,
would you have to recode any variables in any way or create
new variables? Explain what you would do and why.
Part V Data Analysis of your own choosing Using R
(20 points)
Using any data set we have worked with and any variables:
b) Write out the null and research hypotheses connected to this
relationship.
c) Choose an appropriate method to test your hypothesis and
explain/justify your choice.
d) Using R, carry out the test of your hypothesis and explain what
you find
