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 & 5 & 13 & 65 & 25 & 169 \\\\\n \\hdashline\n & 6 & 15 & 90 & 36 & 225 \\\\\n \\hdashline\n & 7 & 18 & 126 & 49 & 324 \\\\\n \\hdashline\n & 9 & 19 & 171 & 81 & 361 \\\\\n \\hdashline\n & 12 & 20 & 240 & 144 & 400 \\\\\n \\hdashline\nSum= & 39 & 85 & 692 & 335 & 1479 \\\\\n \\hdashline\n\\end{array}""\\bar{X}=\\dfrac{1}{n}\\sum _{i}X_i=\\dfrac{62}{9}=6.89"
"\\bar{Y}=\\dfrac{1}{n}\\sum _{i}Y_i=\\dfrac{89}{9}=9.89"
"SS_{XX}=\\sum_iX_i^2-\\dfrac{1}{n}(\\sum _{i}X_i)^2""=335-\\dfrac{39^2}{5}=30.8"
"SS_{YY}=\\sum_iY_i^2-\\dfrac{1}{n}(\\sum _{i}Y_i)^2""=1479-\\dfrac{85^2}{5}=34"
"SS_{XY}=\\sum_iX_iY_i-\\dfrac{1}{n}(\\sum _{i}X_i)(\\sum _{i}Y_i)""=692-\\dfrac{39(85)}{5}=29"
"r=\\dfrac{SS_{XY}}{\\sqrt{SS_{XX}SS_{YY}}}=\\dfrac{29}{\\sqrt{30.8(34)}}""=0.896155"
Strong positive correlation.
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