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Sagot :
The correlation coefficient "r" can take values from -1 to 1
If the correlation coefficient is less than zero, r < 0, the correlation will be considered negative.
If the correlation coefficient is greater than zero, r > 0. the correlation will be considered positive.
A correlation coefficient equal to zero, r = 0, then there is no correlation between both variables.
If the absolute value of the coefficient is less than 0.35: 0 < | r | < 0.35 → you can say that the correlation between the variables is weak or low.
If the absolute value of the coefficient is between 0.35 and 0.38: 0.35 < | r | 0.65 → you can say that the correlation between both variables is moderate.
If the absolute value of the coefficients is greater than 0.66: | r | > 0.66 → you can say that there is a strong/ high correlation between the variables.
If the absolute value of the coefficient is greater than 0.90: | r |>0.90 → You can conclude that the correlation between both variables is very high or marked.
To be able to classify the type of correlation, the first step is to calculate the correlation coefficient between both variables. You can do that manually using the formula:
[tex]r=\frac{\Sigma x_1x_2-\frac{(\Sigma x_1)(\Sigma x_2)}{n}}{\sqrt[]{\lbrack\Sigma x^2_1-\frac{(\Sigma x_1)^2}{n}\rbrack\lbrack\Sigma x^2_2-\frac{(\Sigma x_2)^2}{n}\rbrack}}[/tex]First, let's determine the sums
X₁: Height (in)
[tex]\begin{gathered} \Sigma x_1=20+30+40+40+70+90 \\ \Sigma x_1=290 \end{gathered}[/tex][tex]\begin{gathered} \Sigma x^2_1=20^2+30^2+40^2+40^2+70^2+90^2 \\ \Sigma x^2_1=17500 \end{gathered}[/tex]X₂: Length (in)
[tex]\begin{gathered} \Sigma x_2=18+16+15+16+9+4 \\ \Sigma x_2=78 \end{gathered}[/tex][tex]\begin{gathered} \Sigma x^2_2=18^2+16^2+15^2+16^2+9^2+4^2 \\ \Sigma x^2_2=1158 \end{gathered}[/tex][tex]\begin{gathered} \Sigma x_1x_2=(20\cdot18)+(30\cdot16)+(40\cdot15)+(40\cdot16)+(70\cdot9)+(90\cdot4) \\ \Sigma x_1x_2=3070 \end{gathered}[/tex]There are 5 ordered pairs, so the sample size is n=6
Replace every value on the formula:
[tex]\begin{gathered} r=\frac{3070-\frac{290\cdot78}{6}}{\sqrt[]{\lbrack17500-\frac{290^2}{6}\rbrack\lbrack1158-\frac{78^2}{6}\rbrack}} \\ r=\frac{3070-3861}{\sqrt[]{3483.33\cdot144}} \\ r=-0.99 \\ \end{gathered}[/tex]The correlation coefficient is r= -0.99
→ r is a negative value, which means that the correlation between the height and length of the rectangles is negative
→ the absolute value of the coefficient is greater than 0.90; | r | =0.99, so the correlation between both variables can be considered as a strong correlation
You can say the there is a strong negative correlation between both variables (option F)
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