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SUMMARY OUTPUT Regression Statistics Multiple R 0.993377 R Square 0.986799 Adjusted R Square 0.986359 Standard Error 0.022819 Observations 32 ANOVA df SS MS F Significance F Regression 1 1.167639 1.167639 2242.497 9.37E-30 Residual 30 0.015621 0.000521 Total 31 1.183259 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 3.92966 0.012854 305.7158 5.69E-54 3.903409 3.955911 3.903409 3.955911 X Variable 1 -0.22676 0.004789 -47.355 9.37E-30 -0.23654 -0.21698 -0.23654 -0.21698 Above is a regression analysis of data from a process that is undergoing learning. The initial raw data was entered in minutes. Predict how many minutes the 95th unit will require.

Respuesta :

Answer:

Explained below.

Step-by-step explanation:

From the regression output the regression formed is as follows:

[tex]\hat y=3.92966-0.22676\cdot x[/tex]

Predict how many minutes the 95th unit will require as follows:

[tex]\hat y=3.92966-0.22676\cdot x[/tex]

  [tex]=3.92966-(0.22676\times 95)\\\\=3.92966-21.5422\\\\=-17.61254\\\\\approx 0[/tex]

But time cannot be negative, so the 95th unit will not require much time.

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