MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Please answer all these questions and label, data included:
Size($) | Rent(sq.feet) |
850 | 1950 |
1450 | 2600 |
1085 | 2200 |
1232 | 2500 |
718 | 1950 |
1485 | 2700 |
1136 | 2650 |
726 | 1935 |
700 | 1875 |
956 | 2150 |
1100 | 2400 |
1285 | 2650 |
1985 | 3300 |
1369 | 2800 |
1175 | 2400 |
1225 | 2450 |
1245 | 2100 |
1259 | 2700 |
1150 | 2200 |
896 | 2150 |
1361 | 2600 |
1040 | 2650 |
755 | 2200 |
1000 | 1800 |
1200 | 2750 |
A real estate agent wishes to examine the relationship between the selling price of a home (measured in thousands of dollars) and its size (measured in square feet). In particular she wants to assess if the size of the home can accurately predict the house’s selling price. Use the sample data in the RENT spreadsheet to answer the following questions about the relationship.
- Which characteristic is the dependent variable? Y =
- Which characteristic is the independent variable? X =
- Create a
scatter plot for the data set. What does this tell you about the relationship between the variables?
4. What are the values of the regression coefficients?
- b0 =
- b1 =
5. Write down the equation for the prediction line:
- Yi =
- The value of a house increases on average by how much for each additional one square foot of size?
- When the square footage of a house is 0 ft2, what is the average predicted selling price?
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