x |
y |
23 |
28 |
17 |
20 |
8 |
2 |
29 |
22 |
12 |
18 |
Use the sample data above to answer the following
question. (See exercise 56 on page 160 of your textbook
for a similar problem.)
Compute the correlation.
Sol:
Formula for r is
x | y | xbar | y bar | x-xbar | y-ybar | (x-xbar)(y-ybar) | (x-xbar)^2 | (y-ybar)^2 |
23 | 28 | 17.8 | 18 | 5.2 | 10 | 52 | 27.04 | 100 |
17 | 20 | 17.8 | 18 | -0.8 | 2 | -1.6 | 0.64 | 4 |
8 | 2 | 17.8 | 18 | -9.8 | -16 | 156.8 | 96.04 | 256 |
29 | 22 | 17.8 | 18 | 11.2 | 4 | 44.8 | 125.44 | 16 |
12 | 18 | 17.8 | 18 | -5.8 | 0 | 0 | 33.64 | 0 |
252 | 282.8 | 376 | ||||||
xbar=sumx/n=89/5=17.8 | ||||||||
ybar=sumy/n=90/5=18 | ||||||||
r=252/sqrt(282.8*376) | ||||||||
r=0.7728 |
Alternatively you can find r using software:
install analysis tool pack in excel
go to data>data analysis>correlation
you get
x | y | |
x | 1 | |
y | 0.7728 | 1 |
correlation coefficient=r=0.7728
There exists a strong positive relationship between x and y
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