代写STT 215 – Design of Experiments Homework 7 – Consumer Preference代写数据结构语言程序

STT 215 – Design of Experiments

Homework 7 – Consumer Preference

1.   Conjoint Analysis (5 Points)

a.   What are some disadvantages to using Conjoint Analysis?

b.   How is it used in Segmentation?

2.   (40 Points)

For this problem use the following JMP files: Pizza Profiles.jmp, Pizza Responses.jmp, and Pizza Subjects.jmp.

The profiles table shows there are three factors at two levels each:

Crust: Thick, Thin

Cheese: Mozzarella, Jack

Topping: Pepperoni, None

There were 32 participants evaluating two pizzas at a time and they evaluated 4 pairs for a total of 128 pair comparisons. Their preferences are in the Pizza Responses table. The Pizza Subjects table shows the participants gender.

a.   Determine how many males and females are in the study using Tables/Summary feature. (2 Points)

b.   Using the Analyze/Tabulate feature determine how balanced the design is by creating a two by two table of Choice 1 vs Choice 2.  (4 Points)

c.   Generate a distribution of the preferred Pizza combinations from the raw data (Choice variable from

Pizza Responses table) by using Analyze/Distribution or Graph Builder or Tables/Summary. Provide a summary. (4 Points)

d.  Now model the preference data, analyze the results and provide a summary. (10 Points)

e.   Determine if there are differences between the genders with respect to preference. (In other words rerun d with gender in the model.) (10 Points)

For this section use the following JMP files: Hwk 7 Choice Profiles.jmp and Hwk 7 Choice Runs.jmp.

Through a survey, you will be evaluating 8 scenarios of gym memberships and will be asked to select which one you prefer.  On a separate piece of paper annotate your selection (1, 2, or 3) for the 8 choice sets.

You do not need to record your answers to the other questions.

You will then input your selections in the Hwk 7 Choice Runs.jmp table under the Response column.

Here is the link for the survey: https://redcap.link/m1d9eucc

You will be asked to consider 8 scenarios where each will have 3 gym membership offerings.  The membership options will vary along the following characteristics:

Characteristic	Levels
Trainer	Is trainer part of the membership? Yes / No
Classes	Number of classess offered with the membership: None, 2 or 4
Wait Time	Average wait time in minutes to use machines and equipment 5 mins, 10 mins or 20 mins
Hours	Hours of operation when the gym is available for use 10 AM - 7 PM or 24 Hours
Fees	Additional cost to student per month
Sauna	Is a sauna available? Yes / No
Pool	Is a pool available? Yes / No
Virtual Classes	Are virtual classes offered? Yes / No

3.   (5 Points)

Model your own preference data.

For Profile data, select Hwk 7 Choice Profiles.jmp as the data table.

Profile Id: Choice ID

Grouping: Choice Set

Add all the variables as main effects in the Construct Profile Effects.

For Response Data, select Hwk 7 Choice Runs.jmp table.

Profile Id Chosen: Response

Profile Id Choices: Choice1, Choice2, Choice3

Grouping: Choice Set

Run the model and look at the Utility Profiler.  Analyze the output and provide a summary.

4.   (25 Points)

You will now analyze data with more respondents.  For this section use the following files: Hwk 7 Choice Profiles.jmp, Hwk 7 Full Choice Runs.xlsx and Hwk 7 Subject.txt.  Create JMP tables from the two other  files.

a.   Run the model and summarize the results.

b.   Use the Utility Profiler and summarize your findings.

c.   Set price at $40 and all the other factors utility is at the lowest.  For example, set wait time at 20

minutes.  Record the utility.  Now increase price to $120 / month.  What is the change in utility as you go from $40 to $120?  What is the cost per utility unit?  See slide 55 of Learning Modules/Module 7

Customer Preference Model/Slides and Files/Slides – Consumer Preference deck for help in answering this question.

d.   Consider the Wait Time to use the equipment.  How much more can a gym charge as they go from 20 minutes, to 10 minutes to 5 minutes.

e.   Do a similar analysis as in d for any other factor that was significant.