The accompanying data represent the number of days absent, x, and the final exam score, y, for a sample of college students in a general education course at a large state university. Complete parts (a) through (e) below.
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No. of absences, x |
0 |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
|
---|---|---|---|---|---|---|---|---|---|---|---|
Final exam score, y |
88.9 |
86.4 |
83.7 |
81.5 |
78.9 |
73.2 |
63.7 |
71.8 |
65.1 |
66.8 |
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Click the icon to view the absence count and final exam score data.
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Critical Values for Correlation Coefficient
n
3 0.997
4 0.950
5 0.878
6 0.811
7 0.754
8 0.707
9 0.666
10 0.632
11 0.602
12 0.576
13 0.553
14 0.532
15 0.514
16 0.497
17 0.482
18 0.468
19 0.456
20 0.444
21 0.433
22 0.423
23 0.413
24 0.404
25 0.396
26 0.388
27 0.381
28 0.374
29 0.367
30 0.361
n
(a) Find the least-squaresClick the icon to view a table of
critical values for the correlation coefficient.
regression
line treating number of absences as the explanatory variable and the final exam score as the response variable.
^y=_____x+_____
(Round to three decimal places as needed.)
here i can see that the correlation table is of no use.
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