A mobile phone manufacturer wants to determine the importance of four product attributes (Price, Camera Quality, Battery Life, and Storage Capacity) in the purchase decision of its customers. To achieve this goal, the manufacturer conducted a conjoint analysis study using a fractional factorial design with two levels per attribute. The following table shows the results of the study:

Choice Set	Price	Camera Quality	Battery Life	Storage Capacity	Choice
1	250	Good	Long	64GB	A
1	350	Poor	Short	128GB	B
1	400	Good	Short	64GB	C
2	300	Poor	Long	128GB	A
2	350	Good	Short	64GB	B
2	400	Poor	Short	128GB	C
3	300	Good	Short	128GB	A
3	350	Poor	Long	64GB	B
3	400	Good	Long	64GB	C
4	250	Poor	Long	128GB	A
4	350	Good	Short	128GB	B
4	400	Poor	Short	64GB	C

The utility scores for each level of each attribute were estimated using a linear model as follows:

Utility = Beta0 + Beta1Price + Beta2Camera Quality + Beta3Battery Life + Beta4Storage Capacity

where Beta0 represents the intercept and Beta1 to Beta4 represent the coefficients associated with each attribute.

a) Estimate the utility scores for each level of each attribute using the following beta coefficients: Beta0 = 10, Beta1 = -0.03, Beta2 = 2.2, Beta3 = 1.5, Beta4 = 1.8.

b) Calculate the part-worth utilities for each attribute level.

c) Determine the relative importance of each attribute using the part-worth utilities.

d) Based on the results, what would be the ideal product configuration for the mobile phone manufacturer?

e) Suppose the manufacturer wants to introduce a new product that has a price of $320, a camera quality of "Good", a battery life of "Long", and a storage capacity of "128GB". What is the estimated utility score for this product configuration?