Question
In: Statistics and Probability
1. Use the data of houses in Lancaster to answer the questions below: House price in...
1. Use the data of houses in Lancaster to answer the questions below:
|
House price in $1000s |
Square Feet (X) |
|
245 |
1400 |
|
312 |
1600 |
|
279 |
1700 |
|
308 |
1875 |
|
199 |
1100 |
|
219 |
1550 |
|
405 |
2350 |
|
324 |
2450 |
|
319 |
1425 |
|
255 |
1700 |
b)Find the correlation coefficient? What does the value indicate?
c) Find the coefficient of determination. What does this value indicate?
d)What is the linear regression model?
e)Predict the price of a hose with 2000 square feet
f)Predict the price of a house with 3000 square feet
g)What is the range of interpolation for prediction?
Solutions
Expert Solution
Dear student, we can answer only four subparts at a time, please help to upload other parts separately.
b)
The correlation coefficient comes out to be 0.76. It shows that the two variables are positively and strongly correlated.
c)
It comes out to be 0.58. It shows that the change in the house prices can be 58% explained by the area of the house.
d)
We will be applying the Linear regression model here, it can be done by using the function =LINEST(y_value, x_value, TRUE, TRUE) where y_values contain values of price here and x_values have area values.
Select 5 rows and 2 columns and then write the formula in the first cell and after that, press Shift + Ctrl + Enter.
The equation comes out to be -
Price = 98.25 + 0.11*Area
When area = 2000
Price = 98.25 + 0.11*2000 = 317.78 thousand dollars.
e)
When area = 3000
Price = 98.25 + 0.11*3000 = 427.6 thousand dollars.
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