1. Do the problem below showing all needed JMP or Excel output first. After your output, answer the questions below.
The manager of an auto dealership would like to develop a model to explain the time it takes in days to order in a vehicle with various options. He believes that there is a relationship between the delivery time (in days) and the number of options ordered. Find the data he collected here:
options 3 23 4 17 4 20 7 16 7 8 9 25 12 12 10 14
delivtime 25 66 32 61 26 64 38 58 34 41 39 70 44 41 46 53
a. Describe the relationship shown on the scatterplot.
b. Report the equation of the model for predicting delivery time based upon number of options ordered.
c. Interpret the meaning of the y-intercept.
d. Interpret the meaning of the slope.
e. If a car was ordered with 16 options, how many days would you predict it would take to be delivered? Find the residual for 16 options.
f. Report the coefficient of determination (this is another term for R-squared) and interpret.
g. Report the correlation coefficient and interpret.
h. At the .05 level of significance, is there a linear relationship between number of options ordered and delivery time? Complete a 3 step hypothesis test for correlation to answer this.
i. At the .05 level of significance, is options a significant variable in this model? Complete a 3 step hypothesis test for slope to answer this.
j. Is the data set cross-sectional or time series?
k. Would it be appropriate to predict delivery time for just 2 options ordered? Give an example of a value that it would not be appropriate to predict?
l. What other variables may be useful to include in this model?