Answer to Question #91532 in Statistics and Probability for fahad

Question #91532
In order to determine a relationship between an employee’s age and absenteeism following
random data was selected and presented as following.

Age in years(x) 42 27 36 25 22 39
No. of days absent / years 5 10 8 12 13 7

Required

a) Compute the line of regression
b) Calculate coefficient of correlation (r)
1
Expert's answer
2019-07-09T12:38:28-0400
"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c:c}\n i & x & y & xy & x^2 & y^2 \\\\ \\hline\n 1 & 42 & 5 & 210 & 1764 & 25 \\\\\n \\hdashline\n2 & 27 & 10 & 270 & 729 & 100 \\\\\n \\hdashline\n3 & 36 & 8 & 288 & 1296 & 64 \\\\\n \\hdashline\n4 & 25 & 12 & 300 & 625 & 144 \\\\\n \\hdashline\n5 & 22 & 13 & 286 & 484 & 169 \\\\\n \\hdashline\n6 & 39 & 7 & 273 & 1521 & 49 \\\\\n \\hdashline\n & \\sum x_i=191 & \\sum y_i=55 & \\sum x_iy_i=1627 & \\sum x_i^2= 6419& \\sum y_i^2=551\n\\end{array}"

a) Compute the line of regression 

Calculating the mean "(\\bar{x}, \\bar{y})"


"\\overline{x}={\\sum x_i \\over n}={191 \\over 6}, \\overline{y}={\\sum x_i \\over n}={55 \\over 6}"

The equation of a simple linear regression line (the line of best fit) is y = mx + b,


"m=slope={n\\sum x_iy_i-\\sum x_i \\sum y_i \\over n\\sum x_i^2-(\\sum x_i)^2}"

"m={6\\cdot 1627-191\\cdot 55 \\over 6\\cdot 6419-(191)^2}\\approx -0.365470"

"b=\\overline{y}-m\\overline{x}"

"b\\approx {55 \\over 6}-(-0.365470)\\cdot {191 \\over 6}\\approx 20.800787"

The line of regression 


"y= -0.365470x+20.800787"


b) Calculate coefficient of correlation (r)


"r={n\\sum x_iy_i-\\sum x_i \\sum y_i \\over \\sqrt{n\\sum x_i^2-(\\sum x_i)^2}\\cdot \\sqrt{n\\sum y_i^2-(\\sum y_i)^2}}"

"r={6\\cdot 1627-191\\cdot 55 \\over \\sqrt{6\\cdot 6419-(191)^2} \\sqrt{6\\cdot 551-(55)^2}}\\approx -0.983030"


"r=-0.983030"


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