WTP & Simulations

Due: Nov 04 by 11:59pm

Weight: This assignment is worth 3% of your final grade.

Purpose: The purpose of this assignment is to introduce the concept of willingness to pay (WTP) and to learn how we can use estimated model coefficients to compute estimates of WTP and make predictions about how likely people would be to choose each option in a set of alternatives.

Assessment: This assignment is graded using a check system:

  • ✔+ (110%): Responses shows phenomenal thought and engagement with the course content. I will not assign these often.
  • ✔ (100%): Responses are thoughtful, well-written, and show engagement with the course content. This is the expected level of performance.
  • ✔− (50%): Responses are hastily composed, too short, and/or only cursorily engages with the course content. This grade signals that you need to improve next time. I will hopefully not assign these often.

Notice that this is essentially a pass/fail system. I’m not grading your writing ability and I’m not counting the number of words you write - I’m looking for thoughtful engagement. One or two sentences is not enough. Write at least a paragraph and show me that you did the readings assigned.

1. Get Organized

Follow these instructions:

  1. Download and edit this template.
  2. Unzip the template folder. Make sure you actually unzip it! (in Windows, right-click it and use “extract all”)
  3. Open the .Rproj file to open RStudio.
  4. Inside RStudio, open the hw9.qmd file, take notes, and write some example code as you go through the readings / exercises below.

2. Readings

At this point in the class, we know how to design conjoint surveys, field them on formr.org, clean the resulting data, estimate models, and assess the uncertainty around the resulting coefficients. But what do those coefficients actually mean? How should we use them to gain design insights?

This week, we’ll begin considering these questions as we learn how to use estimated model coefficients to compute estimates of “willingness to pay” (WTP) and make predictions about how likely people would be to choose each option in a set of alternatives. Take notes as you watch the video on these topics, and answer the practice questions in the video as part of your reflection. You may submit your answers however you wish, e.g. hand-write them on paper and take a picture and / or type answers in your reflection .Rmd file.

Click here to download the slides in the video as a PDF.

3. Reflect

Reflect on what you’ve learned while going through these readings and exercises. Is there anything that jumped out at you? Anything you found particularly interesting or confusing? Write at least a paragraph in your hw9.qmd file, and include at least one question. The teaching team will review the questions we get and will try to answer them either in Slack or in class.

If you’re unsure where to start with a reflection, try filling out this template:

“I used to think ______, now I think ______ 🤔”

4. Submit

To submit your assignment, follow these instructions:

  1. Render your .qmd file by either clicking the “Render” button in RStudio or running the command quarto::quarto_render("hw9.qmd") command.
  2. Open the rendered html file and make sure it looks good! Is all the formatting as you expected?
  3. Create a zip file of all the files in your R project folder for this assignment and submit it on the corresponding assignment submission on Blackboard.