Correlation and Regression. This data contains attributes of a random sample of 25 apartment buildings in a city in Minnesota. The price of the apartment building is the dependent variable. Price is expressed in $1,000s (divide PRICE by 1,000). PRICE is thought to be a function of the following independent variables: • #APTS The number of apartments in the building • AGE The age of the apartment building in years • LOTSIZE The lot size that the building is on in square feet The number of parking spaces • PARKING • AREA The total area in square footage • EXCDum This is a dummy variable of the condition of the building. 1= Excellent Condition and O is not Excellent The Correlation Matrix is given below. PRICE #APTS AGE LOTSIZEPARKING AREA EXCDum 1.0000 0.9235 1.0000 -0.1145 -0.0142 1.0000 LOTSIZE 0.7418 0.7997 -0.1909 1.0000 PARKING 0.2249 0.2241 -0.3627 0.1669 1.0000 PRICE #APTS AGE AREA 0.9681 0.8779 0.0270 0.6728 0.0893 1.0000 EXCDum 0.1618 -0.0833 0.1531 -0.2019 -0.1767 0.1992 1.0000 Suppose we regress PRICE on #APTS and PRICE = 101.7862 +15.5253*#APTS generate the following equation: Estimated Based on the equation above, what is the estimated PRICE for an building with 0 apartments? Note that PRICE is expressed per $1,000 and your answer will be expressed as per $1,000. Use four decimal places in your answer and use the proper rules of rounding.

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Correlation and Regression. This data contains attributes of a random sample of 25
apartment buildings in a city in Minnesota. The price of the apartment building is the
dependent variable. Price is expressed in $1,000s (divide PRICE by 1,000).
PRICE is thought to be a function of the following independent variables:
• #APTS The number of apartments in the building
• AGE
The age of the apartment building in years
• LOTSIZE
The lot size that the building is on in square feet
The number of parking spaces
• PARKING
• AREA
The total area in square footage
• EXCDum
This is a dummy variable of the condition of the building. 1= Excellent
Condition and O is not Excellent
The Correlation Matrix is given below.
PRICE #APTS AGE LOTSIZEPARKING AREA EXCDum
1.0000
0.9235 1.0000
-0.1145 -0.0142 1.0000
LOTSIZE 0.7418 0.7997 -0.1909 1.0000
PARKING 0.2249 0.2241 -0.3627 0.1669 1.0000
PRICE
#APTS
AGE
AREA
0.9681 0.8779 0.0270 0.6728 0.0893 1.0000
EXCDum 0.1618 -0.0833 0.1531 -0.2019 -0.1767 0.1992 1.0000
Suppose we regress PRICE on #APTS and
PRICE = 101.7862 +15.5253*#APTS
generate the following equation: Estimated
Based on the equation above, what is the estimated PRICE for an building with 0
apartments? Note that PRICE is expressed per $1,000 and your answer will be expressed as
per $1,000. Use four decimal places in your answer and use the proper rules of rounding.
Transcribed Image Text:Correlation and Regression. This data contains attributes of a random sample of 25 apartment buildings in a city in Minnesota. The price of the apartment building is the dependent variable. Price is expressed in $1,000s (divide PRICE by 1,000). PRICE is thought to be a function of the following independent variables: • #APTS The number of apartments in the building • AGE The age of the apartment building in years • LOTSIZE The lot size that the building is on in square feet The number of parking spaces • PARKING • AREA The total area in square footage • EXCDum This is a dummy variable of the condition of the building. 1= Excellent Condition and O is not Excellent The Correlation Matrix is given below. PRICE #APTS AGE LOTSIZEPARKING AREA EXCDum 1.0000 0.9235 1.0000 -0.1145 -0.0142 1.0000 LOTSIZE 0.7418 0.7997 -0.1909 1.0000 PARKING 0.2249 0.2241 -0.3627 0.1669 1.0000 PRICE #APTS AGE AREA 0.9681 0.8779 0.0270 0.6728 0.0893 1.0000 EXCDum 0.1618 -0.0833 0.1531 -0.2019 -0.1767 0.1992 1.0000 Suppose we regress PRICE on #APTS and PRICE = 101.7862 +15.5253*#APTS generate the following equation: Estimated Based on the equation above, what is the estimated PRICE for an building with 0 apartments? Note that PRICE is expressed per $1,000 and your answer will be expressed as per $1,000. Use four decimal places in your answer and use the proper rules of rounding.
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