An agent for a residential real estate company in a suburb located outside a major city has the business objective of developing more accurate estimates of the monthly rental cost for apartments. Toward the goal, the agent would like to use the size of an apartment, as defined by square footage to predict the monthly rental cost. The agent selects a sample of 8 one-bedroom apartments and the data are shown. Complete parts (a) through (f). 950 1,500 800 1,450 1,900 925 1,800 1,350 Monthly Rent ($) Size (Square Feet) 750 1,250 900 1,250 2,000 750 1,300 1,050 O A. OB. Oc. OD. D. Rent () 2.000 ARen 2,000 2.000 Alen () Alent ( 2.000 2.600 See ( 2.000 Se de 2,600 See (Se o 2.600 See (Se b. Use the least-squares method to determine the regression coefficients bo and b, bo (Round to one decimal place as needed.) b, (Round to one decimal place as needed.) c. Interpret the meaning of b, and b, in this problem. Choose the correct answer below. OA. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Since X cannot be zero, b, has no practical interpretation. O B. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Apartments in this neighborhood cost at least b, dollars. OC. For each increase of 1 square foot in space, the monthly rent is expected to increase by bo dollars. Since X cannot be zero, b, has no practical interpretation. OD. For each increase of 1 square foot in space, the monthly rent is expected to increase by bg dollars. Apartments in this neighborhood cost at least b, dollars. d. Predict the mean monthly rent for an apartment that has 1,000 square feet. The predicted mean monthly rent for such an apartment is s (Round to the nearest cent as needed.) e. Why would it not be appropriate to use the model to predict the monthly rent for apartments that have 500 square feet? O A. An apartment with 500 square feet is outside the relevant range for the independent variable. OB. The size of an apartment has no effect on the monthly rent, according to this model. There must be another factor that contributes to the rent price. OC. The model predicts that the monthly rent for an apartment that has 500 square feet would be unrealistically low. O D. The correlation between an apartment's size and its monthly rent is too weak to use this model for such a prediction.

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
icon
Related questions
Topic Video
Question
An agent for a residential real estate company in a suburb located outside a major city has the business objective of developing more accurate estimates of the monthly rental cost for apartments. Toward the goal, the agent would like to use the size of an apartment, as defined by square footage to predict the monthly rental cost. The agent selects a
sample of 8 one-bedroom apartments and the data are shown. Complete parts (a) through (f).
950 1,500 800 1,450 1,900 925 1,800 1,350 e
Monthly Rent ($)
Size (Square Feet) 750 1,250 900 1,250 2,000 750 1,300 1,050
A.
O A.
O B.
OC.
OD.
ARent ($)
2,000-
ARent (S)
Rent ($)
A
2,000-
ARent (S)
2,000-
2,000-
0-
0+
2,000
Size (sq ft)
2,00
Size (Sq ft)
2,000
Size (Sq ft)
2,000
Size (Sq ft)
b. Use the least-squares method to determine the regression coefficients b, and b,.
b, =
(Round to one decimal place as needed.)
b, = (Round to one decimal place as needed.)
c. Interpret the meaning of b, and b, in this problem. Choose the correct answer below.
O A. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Since X cannot be zero, b, has no practical interpretation.
O B. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Apartments in this neighborhood cost at least b, dollars.
OC. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Since X cannot be zero, b, has no practical interpretation.
O D. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Apartments in this neighborhood cost at least b, dollars.
d. Predict the mean monthly rent for an apartment that has 1,000 square feet.
The predicted mean monthly rent for such an apartment is $
(Round to the nearest cent as needed.)
e. Why would it not be appropriate to use the model to predict the monthly rent for apartments that have 500 square feet?
O A. An apartment with 500 square feet is outside the relevant range for the independent variable.
O B. The size of an apartment has no effect on the monthly rent, according to this model. There must be another factor that contributes to the rent price.
O C. The model predicts that the monthly rent for an apartment that has 500 square feet would be unrealistically low.
O D. The correlation between an apartment's size and its monthly rent is to0 weak to use this model for such a prediction.
Transcribed Image Text:An agent for a residential real estate company in a suburb located outside a major city has the business objective of developing more accurate estimates of the monthly rental cost for apartments. Toward the goal, the agent would like to use the size of an apartment, as defined by square footage to predict the monthly rental cost. The agent selects a sample of 8 one-bedroom apartments and the data are shown. Complete parts (a) through (f). 950 1,500 800 1,450 1,900 925 1,800 1,350 e Monthly Rent ($) Size (Square Feet) 750 1,250 900 1,250 2,000 750 1,300 1,050 A. O A. O B. OC. OD. ARent ($) 2,000- ARent (S) Rent ($) A 2,000- ARent (S) 2,000- 2,000- 0- 0+ 2,000 Size (sq ft) 2,00 Size (Sq ft) 2,000 Size (Sq ft) 2,000 Size (Sq ft) b. Use the least-squares method to determine the regression coefficients b, and b,. b, = (Round to one decimal place as needed.) b, = (Round to one decimal place as needed.) c. Interpret the meaning of b, and b, in this problem. Choose the correct answer below. O A. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Since X cannot be zero, b, has no practical interpretation. O B. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Apartments in this neighborhood cost at least b, dollars. OC. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Since X cannot be zero, b, has no practical interpretation. O D. For each increase of 1 square foot in space, the monthly rent is expected to increase by b, dollars. Apartments in this neighborhood cost at least b, dollars. d. Predict the mean monthly rent for an apartment that has 1,000 square feet. The predicted mean monthly rent for such an apartment is $ (Round to the nearest cent as needed.) e. Why would it not be appropriate to use the model to predict the monthly rent for apartments that have 500 square feet? O A. An apartment with 500 square feet is outside the relevant range for the independent variable. O B. The size of an apartment has no effect on the monthly rent, according to this model. There must be another factor that contributes to the rent price. O C. The model predicts that the monthly rent for an apartment that has 500 square feet would be unrealistically low. O D. The correlation between an apartment's size and its monthly rent is to0 weak to use this model for such a prediction.
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 3 steps with 3 images

Blurred answer
Knowledge Booster
Hypothesis Tests and Confidence Intervals for Means
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.
Similar questions
  • SEE MORE QUESTIONS
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman