The prices (in $) of Rawlston, Inc. stock ( y) over a period of 12 days, the number of shares (in 100s) of company's stocks sold ( x 1), and the volume of exchange (in millions) on the New York Stock Exchange ( x 2) are shown below. Day (y) (x1) (x2) 1 87.50 950 11.00 2 86.00 945 11.25 3 84.00 940 11.75 4 83.00 930 11.75 5 84.50 935 12.00 6 84.00 935 13.00 7 82.00 932 13.25 8 80.00 938 14.50 9 78.50 925 15.00 10 79.00 900 16.50 11 77.00 875 17.00 12 77.50 870 17.50 Excel was used to determine the least squares regression equation. Part of the computer output is shown below. ANOVA df SS MS F Significance F Regression 2 118.8474 59.4237 40.9216 0.0000 Residual 9 13.0692 1.4521 Total 11 131.9167 Coefficients Standard Error t Stat P-value Intercept 118.5059 33.5753 3.5296 0.0064 (x1) -0.0163 0.0315 -0.5171 0.6176 (x2) -1.5726 0.3590 -4.3807 0.0018 a. Use the output shown above and write an equation that can be used to predict the price of the stock. b. Interpret the coefficients of the estimated regression equation that you found in Part a. c. At a .01 level of significance, determine which variables are significant and which are not. d. If on a given day, the number of shares of the company that were sold was 94,500 and the volume of exchange on the New York Stock Exchange was 16 million, what would you expect the price of the stock to be?
Unitary Method
The word “unitary” comes from the word “unit”, which means a single and complete entity. In this method, we find the value of a unit product from the given number of products, and then we solve for the other number of products.
Speed, Time, and Distance
Imagine you and 3 of your friends are planning to go to the playground at 6 in the evening. Your house is one mile away from the playground and one of your friends named Jim must start at 5 pm to reach the playground by walk. The other two friends are 3 miles away.
Profit and Loss
The amount earned or lost on the sale of one or more items is referred to as the profit or loss on that item.
Units and Measurements
Measurements and comparisons are the foundation of science and engineering. We, therefore, need rules that tell us how things are measured and compared. For these measurements and comparisons, we perform certain experiments, and we will need the experiments to set up the devices.
|
Day |
(y) |
(x1) |
(x2) |
|
1 |
87.50 |
950 |
11.00 |
|
2 |
86.00 |
945 |
11.25 |
|
3 |
84.00 |
940 |
11.75 |
|
4 |
83.00 |
930 |
11.75 |
|
5 |
84.50 |
935 |
12.00 |
|
6 |
84.00 |
935 |
13.00 |
|
7 |
82.00 |
932 |
13.25 |
|
8 |
80.00 |
938 |
14.50 |
|
9 |
78.50 |
925 |
15.00 |
|
10 |
79.00 |
900 |
16.50 |
|
11 |
77.00 |
875 |
17.00 |
|
12 |
77.50 |
870 |
17.50 |
Excel was used to determine the least squares regression equation. Part of the computer output is shown below.
| ANOVA | |||||
|
|
df |
SS |
MS |
F |
Significance F |
| Regression |
2 |
118.8474 |
59.4237 |
40.9216 |
0.0000 |
| Residual |
9 |
13.0692 |
1.4521 |
||
| Total |
11 |
131.9167 |
|
|
|
|
|
Coefficients |
Standard Error |
t Stat |
P-value |
|
| Intercept |
118.5059 |
33.5753 |
3.5296 |
0.0064 |
|
| (x1) |
-0.0163 |
0.0315 |
-0.5171 |
0.6176 |
|
| (x2) |
-1.5726 |
0.3590 |
-4.3807 |
0.0018 |
|
| a. | Use the output shown above and write an equation that can be used to predict the price of the stock. | ||||
| b. | Interpret the coefficients of the estimated regression equation that you found in Part a. | ||||
| c. | At a .01 level of significance, determine which variables are significant and which are not. | ||||
| d. | If on a given day, the number of shares of the company that were sold was 94,500 and the volume of exchange on the New York Stock Exchange was 16 million, what would you expect the price of the stock to be? |
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