Skip to main content
Warning: this assignment is out of date. It may still need to be updated for this year's class. Check with your instructor before you start working on this assignment.
This assignment is due before 12:00PM on Tuesday, May 11, 2021.

Analyze Data: Assignment 8 (Optional Extra Credit)

For this assignment, we will analyze data about MTurkers, and try to see if it helps us better understand who/where/when/how questions about crowd workers in the world.

Please download the starter code. It contains three csv files as data, and a jupyter notebook homework8.ipynb with questions, instructions, and skeleton code. Please do not modify any of the function names or input parameters as they are needed for the autograder.


You are provided with the following csv files in this assignment, make sure to upload them to Google Colab before you begin.

  • crowdworker_survey.csv – This file contains almost-clean data collected from a survey taken by crowd workers. For more details, you can check out this paper on how researchers analyze Turker demographics and earnings.

  • clustered_hourly_wage.csv – This contains hourly wage information for each worker.

  • crowd_tasks.csv – This is a random sample of 25,000 tasks from the pool of tasks our survey respondents completed.


Please make sure to submit both the homework8.ipynb and files to Gradescope. We will be manually grading all the plots so double-check that they are saved with your notebook.

You can work in pairs, and each pair only needs to submit one ipython notebook. No report is required.

Grading Rubric

This extra credit assignment can add up to 3% of you overall course grade. For example, if your final grade is 87%, completing this assignment (and get everything right) can bump up your grade to 90%.