A statistics professor would like to build a model relating student scores on the first test to the scores on the second test. The test scores from a random sample of 21 students who have previously taken the course are given in the table.
Student | First Test Grade | Second Test Grade |
---|---|---|
1 | 50 | 70 |
2 | 91 | 58 |
3 | 55 | 74 |
4 | 58 | 65 |
5 | 79 | 60 |
6 | 70 | 60 |
7 | 97 | 48 |
8 | 51 | 73 |
9 | 51 | 73 |
10 | 59 | 66 |
11 | 69 | 67 |
12 | 56 | 70 |
13 | 56 | 73 |
14 | 41 | 76 |
15 | 49 | 72 |
16 | 58 | 68 |
17 | 58 | 73 |
18 | 99 | 53 |
19 | 87 | 58 |
20 | 95 | 50 |
21 | 97 | 55 |
Using statistical software, estimate the parameters of the model
Second Test Grade=β0+β1(First Test Grade)+εiSecond Test
Grade=β0+β1(First Test Grade)+εi.
Enter a negative estimate as a negative number in the regression
model. Round your answers to 4 decimal places, if necessary.
Ans:
Student | First Test Grade | Second Test Grade |
1 | 50 | 70 |
2 | 91 | 58 |
3 | 55 | 74 |
4 | 58 | 65 |
5 | 79 | 60 |
6 | 70 | 60 |
7 | 97 | 48 |
8 | 51 | 73 |
9 | 51 | 73 |
10 | 59 | 66 |
11 | 69 | 67 |
12 | 56 | 70 |
13 | 56 | 73 |
14 | 41 | 76 |
15 | 49 | 72 |
16 | 58 | 68 |
17 | 58 | 73 |
18 | 99 | 53 |
19 | 87 | 58 |
20 | 95 | 50 |
21 | 97 | 55 |
mean= | 67.9048 | 64.8571 |
std. dev= | 18.9971 | 8.5924 |
r= | -0.94997 | |
B1 | -0.4297 | |
B0= | 94.0339 |
Second Test Grade=94.0339-0.4297(First Test Grade)+εi
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