Calculate Karl Pearson’s Coefficient of Correlation X 10 10 11 12 12 y 5 6 4 3
The formula for Karl's Pearson's cCoefficient is:
"r=\\frac{n\\sum_{i=0}^{n}x_iy_i-(\\sum_{i=0}^{n}x_i)(\\sum_{i=0}^{n}y_i)}{\\sqrt{[n\\sum_{i=0}^{n}x^2_i-(\\sum_{i=0}^{n}x_i)^2][n\\sum_{i=0}^{n}y^2_i-(\\sum_{i=0}^{n}y_i)^2]}}"
Since there are 4 values fo y and 5 for x, we assume that the last value is for y 0.
We set n=5 and receive:
"n\\sum_{i=0}^nx_iy_i=5\\cdot(10\\cdot5+10\\cdot6+11\\cdot4+12\\cdot3+12\\cdot0)=950"
"(\\sum_{i=0}^{n}x_i)(\\sum_{i=0}^{n}y_i)=(10+10+11+12+12)(5+6+4+3+0)=55\\cdot18=990"
"n\\sum_{i=0}^{n}x^2_i-(\\sum_{i=0}^{n}x_i)^2=5(10^2+10^2+11^2+12^2+12^2)-(10+10+11+12+12)^2="
"=20"
"n\\sum_{i=0}^{n}y^2_i-(\\sum_{i=0}^{n}y_i)^2=5(5^2+6^2+4^2+3^2+0^2)-(5+6+4+3+0)^2=106"
"r=\\frac{950-990}{\\sqrt{20\\cdot106}}=-0.8687"
Answer:-0.8687
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