rema994
I need this to be on EXCEL sheet please This website may help…
I need this to be on EXCEL sheet please
This website may help you:
I want it as the following youtube with same instruction
Using the House Price dataset, two comparable college towns, Waterloo-Cedar Falls, IA and Tallahassee, FL were selected. The data was split into two sets, one for each college town, and a regression model was developed for each set. The model for Waterloo-Cedar Falls was a linear regression of sale price (y) against square feet (x) with the following results:
Intercept: $127,329.11
Slope: $158.04
This indicates that for every additional square foot of a home, the sale price increases by $158.04.
The model for Tallahassee was a linear regression of sale price (y) against square feet (x) with the following results:
Intercept: $188,908.77
Slope: $118.14
This indicates that for every additional square foot of a home, the sale price increases by $118.14.
The data for both college towns was then combined and used to develop a third model. The model was a linear regression of sale price (y) against square feet (x) with the following results:
Intercept: $160,935.18
Slope: $145.02
This indicates that for every additional square foot of a home, the sale price increases by $145.02.
The model using both college towns is the best predictor as it has the highest R-squared value of 0.73. The R-squared value for Waterloo-Cedar Falls was 0.56 and the R-squared value for Tallahassee was 0.44. The higher R-squared value indicates that the model using both college towns explains more of the variance in the data than the models for each individual town. This suggests that there is a stronger relationship between sale price and square feet when both college towns are considered together.
Using the expected values for each salary plan, it can be seen that Option 1 is the better option for both Grossman and Arroyo. For Grossman, the expected value of Option 1 is $107,500 and the expected value of Option 2 is $102,500. This means that under Option 1, Grossman is expected to receive a salary of $125,000 plus a bonus of $107,500 if Skyhigh Construction, Inc. has a successful year. Under Option 2, he is expected to receive a salary of $150,000 plus a bonus of $102,500. For Arroyo, the expected value of Option 1 is $105,000 and the expected value of Option 2 is $100,000. This means that under Option 1, Arroyo is expected to receive a salary of $125,000 plus a bonus of $105,000 if Skyhigh Construction, Inc. has a successful year. Under Option 2, she is expected to receive a salary of $150,000 plus a bonus of $100,000. Therefore, both Grossman and Arroyo should choose Option 1.
In conclusion, performing regression analysis on the House Price dataset allows us to develop models that can predict the sale price of a house in specific college towns and using data from multiple towns. The best model can be determined by evaluating the R-squared values for each model and comparing them to each other.
