anvas Best Subsets Regression: Ln Cost versus Fou, Decor&Service;,. Response is

Question

anvas Best Subsets Regression: Ln Cost versus Fou, Decor&Service;,. Response is Ln Cost DBP c n sod e z E A FvBS R-Sq R-Sq o cc a Vars R-Sq (adj) (pred) Mallows Cp s dek n 1 78.7 78.4 1 60.8 60.2 1 51.0 50.348. 29.4 58.6 375.6 0.23654 743.70.32098 944.0 0.35866 X 1 5.7 4.3 0.0 79.6 2 94.7 94.5 78.9 2 83.583.0 41.3 58.8 97.0 96.9 88.0 95.0 94.7 78.4 1873.9 0.49753 2 94.9 94.7 5.3 0.11693 x x 49.30.11917x X 278.90.20981 696.5 0.31348 x X 2 63.2 62.0 45.6 0.11694 XXX 50.0 0-11941 X 94 94.5 59.5 87.2 652.7 0.30527 .xx 6.8 0 0.090463 x xx x

Explanation / Answer

Q1) R-Squared – used to propose perfection of model prediction

R-Squared (Adju) – Improvement in the regression model in increase or decrease of r-squared.

s- Standard of error: on regressions Standard of error used to calculate the least error

Mallows Cp: Assess fits when a model with different criteria of parameters and be used to estimate least squares.

R-squared(Prediction): Will not be considered for predictions

Answer: D(R-Squ(Pred)

Q2) With 78.7 R-squared value- Bang for Buck

Q3) R squared value:

Food with Décor- 63.2(R sq) – 62(Adj R squ)

Decor with bang – 94.7(R sq)-94.5 (Adj R squ)

Bang with Type food – 83.5(R sq)-83 (Adj R squ)

Food with Bang – 94.9(R sq) – 94.7 (Adj R squ)

Answer: D

Q4)

Food, Décor, Bang- 97.0 (R-Sq)– 96.9(Adj R squ)

Décor, Bang, Type food – 94.7 R sq) -94.5(Adj R squ)

Food, Bang, Type food –95 R sq) - 94.7(Adj R squ)

Food, Décor, Type food – 65.4 R sq) -63.7(Adj R squ)

Answer: A

Q5)

Food- Décor & Service- Bang for Buck

R Square- 97.0

Adj R square- 96.9

S- 0.089763

Mallows Cp – 3.0

This model has high accuracy than other models.

Q6)

With least R-squared and Adj R –Sqaured – Type food Asian

Answer: D

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