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4. Data on 88 house sales have been collected. For each sold house, the following variables are available: PRICE the price the house was sold

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4. Data on 88 house sales have been collected. For each sold house, the following variables are available: PRICE the price the house was sold at (in $1000 s) ASSESS the assessment value of the house (in $1000 s) LOTSIZE lot size (in 100sq. ft.) SQRFT house square footage (in 100sq. ft.) BDRMS the number of bedrooms (a) Consider the model PRICE=0+1ASSESS+2LOTSIZE+3SQRFT+4BDRMS+u. OLS results are as follows: Other things being fixed, does adding another bedroom increase the price by $20,000 ? Write down the null and alternative hypotheses, perform the test and interpret the result. (b) Suppose you have been asked to test whether lot size, square footage and the number of bedrooms jointly have an effect on price for a given assessment value. The following regression is available: - reg prico assess Write down the corresponding null and alternative hypotheses, perform the test and interpret the results. 4. Data on 88 house sales have been collected. For each sold house, the following variables are available: PRICE the price the house was sold at (in $1000 s) ASSESS the assessment value of the house (in $1000 s) LOTSIZE lot size (in 100sq. ft.) SQRFT house square footage (in 100sq. ft.) BDRMS the number of bedrooms (a) Consider the model PRICE=0+1ASSESS+2LOTSIZE+3SQRFT+4BDRMS+u. OLS results are as follows: Other things being fixed, does adding another bedroom increase the price by $20,000 ? Write down the null and alternative hypotheses, perform the test and interpret the result. (b) Suppose you have been asked to test whether lot size, square footage and the number of bedrooms jointly have an effect on price for a given assessment value. The following regression is available: - reg prico assess Write down the corresponding null and alternative hypotheses, perform the test and interpret the results

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