Questions:

1. Calculate the mean, median, mode and standard deviation for three variables of your choice contained in the data set.

2. Calculate the coefficient of correlation and coefficient of determination for all the possible pairs of the three identified variables.

3. Create a multiple linear regression equationfrom the dataset with choosing your ownY-variable and at least three X-variables.

a. What is its Adjusted R-Squared?

b. What is the predicted value of your Y variable for the most recent year +1, i.e., (n+1)? For example, if the most recent year of your data set is 2016, you should predict the value for 2017.

c. What can you say about the p-values of the regression coefficients?

4. Create linear and quadratic time series regressions to model one of the X variables. There is no need to deseasonalize the data through dummy variables or seasonal factors.

a. What is the RMSE of each of the two models?

b. What is the predicted value of chosen X variable for the most recent year +2, i.e., (n+2)? For example, if the most recent year of your data set is 2016, you should predict the value for 2018.

5. Analyze Question #3 and #4 of the above and explain your assumptions and reasoning.