Reference no: EM131228273

Assignment:  Business Statistics

PART A: Question 1 - Case Study

Predicting the selling price of houses in the city of Baycoast

The management of the agency are particularly interested in the rating of the street and suggest that you develop a model to investigate the relationship between house prices and rating of the street in which the house is located.

From a sample of 120 houses the above excel output was obtained.  To help the management of BCREA to make decisions, answer the following questions:

a) Determine the equation of the least squares regression line and explain the regression equation.

b) What is the standard error of the estimate (Se)?  Comment on the size of the standard error for this regression model.

c) Test the slope of the regression line and what do you conclude about the slope?

d) What is the coefficient of determination for this model?  Does street rating appear to be a good predictor of house prices?  Why or why not?

e) Finally, write a very brief report based on the information available for management.

PART B -

Question 1 - The city commission is considering raising property taxes to finance a new library.  The commission feels they should tax only those who own homes valued in the top 40 percent.  If property values can be expressed as X ∼ N($62,500, $8,250), what is the highest value that can be placed on a property without being subjected to the tax?

Question 2 - The average life expectancy of males in a developing nation was believed to be 62.5 years.  However, the belief was based on data that might be considerably out of date.  A random survey of 250 deaths in that country revealed an average life span of 64.2 years with a standard deviation of 8.8 years.  Does the sample evidence indicate that the mean life expectancy defers from 62.5 years?  Use a significance level of 0.05.

Attachment:- Case Study.rar