A. Use the given Regression Analysis to write a regresion equation for the data.

Question

A. Use the given Regression Analysis to write a regresion equation for the data.

B. Using the equation from "Regression Analysis", Go to the worksheet "VALIDATION", and predict the Output values for given input variables.

SUMMARY OUTPUT Rearession Statistics MultipleR R Square Adjusted R Square0.45978659 Standard Error Observations 0.688662901 0.474256592 1116.54891 225 ANOVA Significance F 245161086.3 40860181 32.775165.13822E-28 MS Regression Residual Total 6 218 224516937646.2 271776560 1246681 Intercept X Variable 1 X Variable 2 X Variable 3 X Variable 4 X Variable 5 X Variable 6 Coefficients Standard Error tstat P-value Lower 95% U er95% Lower 95.0% Uper 95.0% 17129.547516111.25318 1.063204 0.288866-14624.21078 48883.30588-14624.21078 48883.30588 387.988711 2.83077 0.005078 1862.996155 -333.6179465-1862.996155333.6179465 384.782952 2.815512 0.005316 324.990301 1841.732013 324.990301 1841.732013 13.89034396 41.93119339 0.331265 0.740762-68.75207786 96.53276579 -68.75207786 96.53276579 3276.98262 6984.218973 -0.4692 0.639397-17042.21857 10488.2533217042.21857 10488.25332 2127.2367621448.799668-1.46828 0.1434714982.68407 728.210546-4982.68407 728.210546 -41.66598359 6.037952514-6.90068 5.55E-11-53.56621771-29.76574946-53.56621771-29.76574946 -1098.307051 1083.361157

Explanation / Answer

Solution1:

A. Use the given Regression Analysis to write a regresion equation for the data.

regression eq from the output is

y=17129.54755-1098.307051* X Variable1+1083.361157* X variable 2

+13.89034396* X variable 3 -3276.98262* X variable 4-2127.236762* X variable 5

-41.66598359* X variable 6

SolutionB:

provide Output values for given input variable

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