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A Random Sample of 76 Apartments Is Collected near a University

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A random sample of 76 apartments is collected near a university. All of the apartments in the sample have between 1 and 6 bedrooms. The variables recorded for each apartment are Rent (in dollars) and the number of Bedrooms. The regression output is:
The dependent variable is Rent
R squared =62.0%= 62.0 \% \quad R squared (adjusted) =61.5%= 61.5 \%
s=364.4\mathrm { s } = 364.4 with 762=7476 - 2 = 74 degrees of freedom

 Variable  Coeff  SE(Coeff)  t-ratio  p-value  Constant 357.795111.63.20.0020 Bedrooms 400.55436.4211.0<0.0001\begin{array} { l c c r r } \text { Variable } & \text { Coeff } & \text { SE(Coeff) } & \text { t-ratio } & \text { p-value } \\ \text { Constant } & 357.795 & 111.6 & 3.2 & 0.0020 \\ \text { Bedrooms } & 400.554 & 36.42 & 11.0 & < 0.0001 \end{array}
a. Write out the regression equation.
b. Compute a 95% confidence interval for the coefficient of Bedrooms. Explain your
confidence interval in the context of the problem.
c. Based on your interval is the number of bedrooms a significant predictor of rent? Explain
how you reached your answer.
d. Explain the meaning of the regression intercept in the context of this problem.
e. Use the plots below to check the regression conditions.  A random sample of 76 apartments is collected near a university. All of the apartments in the sample have between 1 and 6 bedrooms. The variables recorded for each apartment are Rent (in dollars) and the number of Bedrooms. The regression output is: The dependent variable is Rent R squared  = 62.0 \% \quad  R squared (adjusted)  = 61.5 \%   \mathrm { s } = 364.4  with  76 - 2 = 74  degrees of freedom   \begin{array} { l c c r r } \text { Variable } & \text { Coeff } & \text { SE(Coeff) } & \text { t-ratio } & \text { p-value } \\ \text { Constant } & 357.795 & 111.6 & 3.2 & 0.0020 \\ \text { Bedrooms } & 400.554 & 36.42 & 11.0 & < 0.0001 \end{array}   a. Write out the regression equation. b. Compute a 95% confidence interval for the coefficient of Bedrooms. Explain your confidence interval in the context of the problem. c. Based on your interval is the number of bedrooms a significant predictor of rent? Explain how you reached your answer. d. Explain the meaning of the regression intercept in the context of this problem. e. Use the plots below to check the regression conditions.


Definitions:

Geographic Design

The strategic arrangement of physical locations, facilities, and infrastructure to optimize an organization’s operations across different geographic areas.

Product Design

The process of conceptualizing and creating a new product to be sold by a business to its customers, focusing on functionality, appearance, and user experience.

Network Design

The planning and structuring of a network, including the physical and logical layout, to meet specific operational requirements and goals.

Geographic Design

Pertains to the planning and arrangement of physical space or structure considering geographic factors like location and environmental conditions.

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