In each paragraph, the following should be addressed:
How is the variable defined in the data source?
Which unit of measurement is used?
For the independent variables: why does the variable determine Y?
What sign is expected for the independent variable’s coefficient, positive or negative? Why?
5) In one paragraph, describe the data and identify the data sources.
From which general sources and from which specific tables are the data taken? (Citing a website is not acceptable.)
Which year or years were the data collected?
Are there any data limitations?
Presentation and Interpretation of Results
6) Write the regression (prediction) equation:
Dep_Var = Intercept + c1 * Ind_Var_1 + c2 * Ind_Var_2 + c3* Ind_Var_3
7) Identify and interpret the adjusted R2 (one paragraph):
Define “adjusted R2.”
What does the value of the adjusted R2 reveal about the model?
If the adjusted R2 is low, how has the choice of independent variables created this result?
8) Identify and interpret the F test (one paragraph):
Using the p-value approach, is the null hypothesis for the F test rejected or not rejected? Why or why not?
Interpret the implications of these findings for the model.
9) Identify and interpret the t tests for each of the coefficients (one separate paragraph for each variable, in numerical order):
Are the signs of the coefficients as expected? If not, why not?
For each of the coefficients, interpret the numerical value.
Using the p-value approach, is the null hypothesis for the t test rejected or not rejected for each coefficient? Why or why not?
Interpret the implications of these findings for the variable.
Identify the variable with the greatest significance.
10) Analyze multicollinearity of the independent variables (one paragraph):
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