Preference learning and Homework 2
by Max Yi Ren
See the lecture notes, the Qualtrics tutorial, and this engineer-friendly tutorial (Part 1, Part 2) on discrete choice analysis.
Activity 1: Test the survey
Please participate in a mock survey regarding your preference on cars. Once we collect the data, we will go through a data analysis procedure called discrete choice analysis, from where quantified preference on attribute levels can be revealed for the participant group as a whole and for individual participants.
Homework 2: Conduct a market survey and report your analysis results
The report should contain the following elements:
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A description of your survey goal, i.e., what do you want to learn from your consumer group? This could include qualitative goals, and quantitative hypotheses.
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A description of design attributes and attribute levels
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A complete sample survey and a discussion on how questions are designed
- A description of how data is collected
- Who do you collect data from?
- When is the data collected?
- Are your collected data valid? How do you validate?
- A description of how the data is analyzed
- What preprocess steps are necessary for your data?
- For discrete choice analysis, how do you set up your model and what assumptions do you use?
- What results do you get from your analysis?
- What insights do you get from your analysis?
- From these insights, how will you improve your survey?
- Please provide a visualization of your results. Simply pasting MATLAB tables to your report will not be accepted.
- The code and raw data you used for the analysis
- Make sure that by directly running your code with your data, others can reproduce your results.
Notes:
- Submit your report to yiren@asu.edu with the exact title “MAE540 Homework 2 - Team number”. Please make sure it is in pdf format.