QUESTION IMAGE
Question
question number 3. determine the correlation coefficient for the data shown in this table:
| y | x |
|---|---|
| 29 | 4 |
| 28 | 10 |
| 40 | 15 |
| 34 | 13 |
| 43 | 16 |
o 0.8332
o 0.4564
o -0.9128
o 0.9128
o -0.8332
o none of the above
Step1: Recall correlation - coefficient formula
The Pearson correlation coefficient $r$ is given by the formula:
\[r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^{2}-(\sum x)^{2}][n\sum y^{2}-(\sum y)^{2}]}}\]
First, calculate the necessary sums:
Let $n = 6$.
| $y$ | $x$ | $xy$ | $x^{2}$ | $y^{2}$ |
|---|---|---|---|---|
| 29 | 4 | 116 | 16 | 841 |
| 28 | 10 | 280 | 100 | 784 |
| 40 | 15 | 600 | 225 | 1600 |
| 34 | 13 | 442 | 169 | 1156 |
| 43 | 16 | 688 | 256 | 1849 |
$\sum x=2 + 4+10 + 15+13+16=60$
$\sum y=22 + 29+28+40+34+43=196$
$\sum xy=44 + 116+280+600+442+688=2170$
$\sum x^{2}=4 + 16+100+225+169+256=770$
$\sum y^{2}=484+841+784+1600+1156+1849=6714$
Step2: Substitute into the formula
\[n(\sum xy)-(\sum x)(\sum y)=6\times2170-60\times196\]
\[=13020 - 11760=1260\]
\[n\sum x^{2}-(\sum x)^{2}=6\times770-60^{2}\]
\[=4620 - 3600 = 1020\]
\[n\sum y^{2}-(\sum y)^{2}=6\times6714-196^{2}\]
\[=40284-38416 = 1868\]
\[r=\frac{1260}{\sqrt{1020\times1868}}\]
\[=\frac{1260}{\sqrt{1905360}}\]
\[=\frac{1260}{1380.3477}\approx0.9128\]
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0.9128