Мирончук Евгений / Kursovoi / Эксперимент

Multiple Regression Analysis

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Dependent variable: Y

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Standard T

Parameter Estimate Error Statistic P-Value

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CONSTANT -1,18349 0,38885 -3,04357 0,0112

x1 -0,063581 0,00621774 -10,2257 0,0000

x2 -0,0241348 0,00518145 -4,65792 0,0007

x3 0,484981 0,0310887 15,5999 0,0000

x4 -0,0409676 0,00310887 -13,1777 0,0000

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Analysis of Variance

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Source Sum of Squares Df Mean Square F-Ratio P-Value

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Model 8,40119 4 2,1003 135,82 0,0000

Residual 0,170105 11 0,0154641

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Total (Corr.) 8,5713 15

R-squared = 98,0154 percent

R-squared (adjusted for d.f.) = 97,2937 percent

Standard Error of Est. = 0,124355

Mean absolute error = 0,0853816

Durbin-Watson statistic = 1,53346

The StatAdvisor

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The output shows the results of fitting a multiple linear

regression model to describe the relationship between Y and 4

independent variables. The equation of the fitted model is

Y = -1,18349 - 0,063581*x1 - 0,0241348*x2 + 0,484981*x3 - 0,0409676*x4

Multiple Regression Analysis

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Dependent variable: Y

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Standard T

Parameter Estimate Error Statistic P-Value

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CONSTANT -1,34527 0,389631 -3,45268 0,0054

x1 -0,0662481 0,0023264 -28,4766 0,0000

x2 -0,0263183 0,0017448 -15,0838 0,0000

x3 0,515653 0,034896 14,7768 0,0000

x4 -0,0484844 0,00139584 -34,7349 0,0000

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Analysis of Variance

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Source Sum of Squares Df Mean Square F-Ratio P-Value

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Model 1,91978 4 0,479944 615,83 0,0000

Residual 0,00857285 11 0,00077935

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Total (Corr.) 1,92835 15

R-squared = 99,5554 percent

R-squared (adjusted for d.f.) = 99,3938 percent

Standard Error of Est. = 0,0279168

Mean absolute error = 0,0187224

Durbin-Watson statistic = 2,08996

The StatAdvisor

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The output shows the results of fitting a multiple linear

regression model to describe the relationship between Y and 4

independent variables. The equation of the fitted model is

Y = -1,34527 - 0,0662481*x1 - 0,0263183*x2 + 0,515653*x3 - 0,0484844*x4