In order to compute the regression coefficients, the following table needs to be used:
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c:c}\n & X & Y & XY & X^2 & Y^2 \\\\ \\hline\n & 2 & 8 & 16 & 4 & 64 \\\\\n \\hdashline\n & 4 & 10 & 40 & 16 & 100 \\\\\n \\hdashline\n & 6 & 12 & 72 & 36 & 144 \\\\\n \\hdashline\n & 7 & 6 & 42 & 49 & 36 \\\\\n \\hdashline\n & 10 & 16 & 160 & 100 & 256 \\\\\n \\hdashline\nSum= & 29 & 52 & 330 & 205 & 600 \\\\\n \\hdashline\n\\end{array}"
"\\bar{X}=\\dfrac{1}{n}\\sum _{i}X_i=\\dfrac{29}{5}=5.8"
"\\bar{Y}=\\dfrac{1}{n}\\sum _{i}Y_i=\\dfrac{52}{5}=10.4"
"SS_{XX}=\\sum_iX_i^2-\\dfrac{1}{n}(\\sum _{i}X_i)^2""=205-\\dfrac{29^2}{5}=36.8"
"SS_{YY}=\\sum_iY_i^2-\\dfrac{1}{n}(\\sum _{i}Y_i)^2""=600-\\dfrac{(52)^2}{5}=59.2"
"SS_{XY}=\\sum_iX_iY_i-\\dfrac{1}{n}(\\sum _{i}X_i)(\\sum _{i}Y_i)""=330-\\dfrac{29(52)}{5}=28.4"
"r=\\dfrac{SS_{XY}}{\\sqrt{SS_{XX}SS_{YY}}}=\\dfrac{28.4}{\\sqrt{36.8(59.2)}}"
"=0.608462"
"0.4<r<0.7" Moderate positive correlation
"m=slope=\\dfrac{SS_{XY}}{SS_{XX}}=\\dfrac{28.4}{36.8}=0.7717""n=\\bar{Y}-m\\bar{X}=10.4-\\dfrac{28.4}{36.8}(5.8)=5.9239"
The regression equation is:
"y=5.9239+0.7717x"
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