Given the following table, answer the questions

SUMMARY OUTPUT FROM A MODEL OF THE FORM:

LN(Y) = LN(O) + t LN(1)

Regression Statistics

Multiple R 0.96408358

R Square 0.92945714

Adjusted R Square 0.89418571

Standard Error. 0.02012143

Observations. 4

ANOVA

df SS

Regression 1 0.01066901

Residual 2 0.00080974

Total 3 0.01147876

Coefficients Standard Error

Intercept 2.21673153 0.0168348

Coded Year 0.0461931 0.00899858

RESIDUAL OUTPUT

Observation Predicted lnR Residuals

1 2.21673153 0.01328287

2 2.26292463 -0.0116328

3 2.30911772 -0.016583

4. 2.35531082 0.01493292

The MAD from the model that you would compare to a linear model is equal to:

1.50

1.00

5.13

0.014