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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.

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