The accompanying multiple regression model was developed to relate receipts (rev

Question

The accompanying multiple regression model was developed to relate receipts (revenue) of Broadway plays to the number of paying attendants, the number of shows, and the average ticket price. A hypothesis test (alpha = 0.05) for the true coefficient of # Shows with H_0 middot rho_Shows = 0 and H_A middot rho_Shows notequalto 0 produced a p-value of 0 413 and the null hypothesis was not rejected. An investor accepts this analysis but claims that it demonstrates that it doesn't matter how many shows are playing on Broadway receipts will be essential the same. Explain why this interpretation is not a valid use of this regression model. Be specific. Explain why this interpretation is not a valid use of this regression model. Select all appropriate responses below. This interpretation attempts to interfere a coefficient without taking account of the other variables in the model. The investors causal interpretation is backwards the number of shows will be about the same regardless of the receipts. The hypothesis test implied that the number of shows had a significant impact on the receipts. This is a casual interpretation, which is not supported by regression.

Explanation / Answer

The given interpretation of is not valid to use of the regression model because this interpretation attempts to interpret a coefficient without taking account of the other variables in the model.

Answer is "A"

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