In: Statistics and Probability
1. Use the data below.
Date | DOW | S&P500 |
8-Apr-20 | 23,719.37 | 2,789.82 |
1-Apr-20 | 22,653.86 | 2,659.41 |
25-Mar-20 | 21,917.16 | 2,584.59 |
18-Mar-20 | 20,704.91 | 2,447.33 |
11-Mar-20 | 21,237.38 | 2,529.19 |
4-Mar-20 | 25,018.16 | 2,882.23 |
26-Feb-20 | 25,917.41 | 3,003.37 |
19-Feb-20 | 27,081.36 | 3,128.21 |
12-Feb-20 | 29,232.19 | 3,370.29 |
5-Feb-20 | 29,276.34 | 3,357.75 |
29-Jan-20 | 28,807.63 | 3,297.59 |
22-Jan-20 | 28,722.85 | 3,276.24 |
15-Jan-20 | 29,196.04 | 3,320.79 |
8-Jan-20 | 28,939.67 | 3,283.15 |
1-Jan-20 | 28,583.68 | 3,237.18 |
c. Suppose that the closing price for the DOW is 29,000.
Estimate the closing price for your data for
April.a.. Use the data to develop an estimated
regression equation showing how your team data is related to DOW,
the Dow Jones industrial average. What is the estimated regression
model?
Let x represent the DOW indexes.
b. How much of the variation in the sample values of
your team data does the model estimated in part (b) explain?
Round your answer to two decimal places.
d. Preform a hypothesis test for the model (F test) with an significance of 0.05. State your conclusion.
e. Preform a hypothesis test for each of the estimated coefficients at the 0.05 level of significance. State your conclusions.