Chapter 3 Case Problem



Chapter 12 Case Problem Simple Linear Regression Modeling

Real estate brokers are continually assessing how much the sales prices of condominiums are influenced (if any) by the amount of time (in weeks) that a condo stays on the market. The brokers believe that the longer a condo stays on the market, the lower the relative sales price will be. Sales data was collected over a several year period to test if there is in fact a relationship between sales price and time on market (in weeks). Below is a sample of the data from the data set. The variable ‘Weeks on the Market’ represents how long a condo stayed on the market before it was sold. The variable ‘Selling Price’ is the final price for which the condo was sold.

|Weeks on the Market |Selling Price |

|23 |$ 243,270 |

|48 |$ 324,360 |

|9 |$ 168,540 |

|26 |$ 267,756 |

|20 |$ 232,140 |

|40 |$ 397,500 |

|… |… |

|… |… |

|… |… |

|15 |$ 298,697 |

Download the complete data set from the course website.

Create a Managerial Report summarizing and analyzing the data set. Use the template provided in the Excel data file. Do not modify/change the template.

1. Construct a descriptive summary for each variable in the data set.

2. Is this data set a good data set for simple linear regression? Explain.

3. Use regression analysis to develop an estimated regression equation that could be used to predict the condo selling price based on the number of weeks that the condo remained on the market.

4. What conclusions and recommendations can you derive from your analysis using an alpha of 0.01?

5. All other aspects of the condo being the same, how much would you expect a condo to sell for if it were on the market for 37 weeks?

................
................

In order to avoid copyright disputes, this page is only a partial summary.

Google Online Preview   Download