The director of graduate studies would like to predict
the grade point average (GPA) of students in MBA program based on the Graduate
Management Admission Test (GMAT) score. The results are stored in the table below
A sample of 20 students who had completed 2 years in the program is selected.
GMAT	GPA
690	3.74
650	3.58
594	3.33
680	3.91
617	3.28
557	3.02
599	3.13
625	3.58
694	3.60
643	3.65
580	3.05
688	3.72
647	3.44
652	3.21
598	3.15
551	2.91
563	2.65
520	2.81
730	3.92
759	3.76
a) Construct a scatter plot
b) State the linear regression equation as y = b0 + b1x
c) Interpret the meaning of the b0 and b1 in this problem
d) Predict the GPA for a student with GMAT score 650.
e)Calculate and graph the regression line on the scatter plot.
f) Perform t-test to see if the slope is significant
Problem 2.	neighbor.xls	Problem 14.40 page 599
		Problem40 page 191
A real estate agent wants to study the relationship between the number of rooms
in a single-family house and the selling price of the house (in thousands of dollars).
Two neighborhoods are included in the study ,
one on the east side (=0) and the other on the west side (=1).
A random sample of 18 houses is given in the table below.
Price	Rooms	Neighborhood
309.6	7	east
307.4	8	east
342.4	9	west
323.7	8	west
319.3	9	east
337.8	9	east
314.8	10	east
313.2	8	east
327.8	9	east
381.3	13	west
337.4	10	west
346.2	10	west
343.6	9	west
360.7	11	west
330.4	8	east
297.5	6	east
320.5	8	west
298.2	6	east
a) State the multiple regression equation as y = b0 + b1x1 + b2x2
b) Interpret the meaning of the slopes in this problem.
c) Predict the selling price for a house with 8 rooms that is located in an west-side neighborhood.
d) Calculate the multiple and adjusted coefficients of determination.
Using the SS variations from the DA.
e) Compute coefficients of partial determination due to each independent variable
f) Add an interaction term to the model and determine whether it makes a significant
contribution to the model.	( based on p-value )
Problem 3	taxes.xls	Pr 15.5 page 621
		Pr 5 page 219
An auditor for a county government would like to develop a model
to predict the county taxes, based on the age of a single-family house.
The 22 houses were selected and given in the table below. Assume a quadratic relationship
between the age and county taxes.
Taxes	Age
925	1
870	2
789	3
720	4
694	5
630	8
626	10
546	12
523	15
480	20
486	22
475	23
469	21
459	26
441	25
426	30
450	45
350	40
348	50
335	47
315	48
315	58
a) Construct a scatter plot between age and county taxes.
b) State the quadratic regression equation as y = b0 + b1x1 + b2 x^2
Graph the least-square curve on the scatter plot of a)
c) Predict the mean county taxes for a house that is 22 years old.
d) Find the linear model and compare the residuals of it with the residuals of the quadratic model.
e) Compare the linear and quadratic models and determine whether the quadratic term improves the model. Explain.
	Do p value and slope interval tests. Use R^2 of the models.