In: Math
1. Consider the first and second exam scores of the 10 students listed below. Calculate the Pearson's correlation coefficient for the dataset below and interpret what that means.
exam 1 | exam 2 |
24 | 37 |
22 | 35 |
21 | 42 |
22 | 40 |
21 | 41 |
23 | 37 |
23 | 30 |
23 | 37 |
21 | 48 |
25 | 30 |
A)The correlation is -0.774 . There is a strong negative linear association between Exam 1 and Exam 2
B) The correlation is -0.774 . There is a weak negative linear association between Exam 1 and Exam 2 .
C)The correlation is 0.774 . There is a strong positive linear association between Exam 1 and Exam 2 .
D)The correlation is -0.774 . There is a strong positive linear association between Exam 1 and Exam 2 .
E)The correlation is 0.774 . There is a strong negative linear association between Exam 1 and Exam 2 .
2. Consider the first and second exam scores of the 10 students listed below. Calculate the Pearson's correlation coefficient for the data set below and interpret what that means.
exam 1 | exam 2 |
23 | 29 |
29 | 24 |
19 | 19 |
17 | 27 |
24 | 22 |
10 | 20 |
29 | 28 |
20 | 18 |
25 | 18 |
16 |
29 |
A)The correlation is 0.147 . There is a weak negative linear association between Exam 1 and Exam 2 .
B)The correlation is -0.147 . There is a weak positive linear association between Exam 1 and Exam 2
C)The correlation is 0.147 . There is a strong positive linear association between Exam 1 and Exam 2
D)The correlation is -0.147 . There is a weak negative linear association between Exam 1 and Exam 2
E)
The correlation is 0.147 . There is a weak positive linear association between Exam 1 and Exam 2 . |
Question 1
Exam 1 (X) | Exam 2 (Y) | X * Y | X2 | Y2 | |
24 | 37 | 888 | 576 | 1369 | |
22 | 35 | 770 | 484 | 1225 | |
21 | 42 | 882 | 441 | 1764 | |
22 | 40 | 880 | 484 | 1600 | |
21 | 41 | 861 | 441 | 1681 | |
23 | 37 | 851 | 529 | 1369 | |
23 | 30 | 690 | 529 | 900 | |
23 | 37 | 851 | 529 | 1369 | |
21 | 48 | 1008 | 441 | 2304 | |
25 | 30 | 750 | 625 | 900 | |
Total | 225 | 377 | 8431 | 5079 | 14481 |
r = -0.774
A)The correlation is -0.774 . There is a strong negative linear association between Exam 1 and Exam 2
Question 2
Exam 1 (X) | Exam 2 (Y) | X * Y | X2 | Y2 | |
23 | 29 | 667 | 529 | 841 | |
29 | 24 | 696 | 841 | 576 | |
19 | 19 | 361 | 361 | 361 | |
17 | 27 | 459 | 289 | 729 | |
24 | 22 | 528 | 576 | 484 | |
10 | 20 | 200 | 100 | 400 | |
29 | 28 | 812 | 841 | 784 | |
20 | 18 | 360 | 400 | 324 | |
25 | 18 | 450 | 625 | 324 | |
16 | 29 | 464 | 256 | 841 | |
Total | 212 | 234 | 4997 | 4818 | 5664 |
r = 0.147
E)
The correlation is 0.147 . There is a weak positive linear association between Exam 1 and Exam 2 . |