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This assignment is before 11:59PM due on Thursday, April 11, 2019.

Analyze Data: Assignment 8

We are down to the final two weekly homework assignments. This week, we will analyze the data about MTurkers, and try to see if it better helps us answer who/where/when/how questions about crowd workers in the world.

Please download here to start. It contains four csv files as data, and an ipython notebook HW8.ipynb with questions, instructions and skeleton code.

Data

You will be provided the following csv files in this assignment:

  • 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.

  • work_time_pay.csv – This file contains average task completion time and average pay per task for a subset of workers from the original data in crowdworker_survey.csv.

Deliverables

One deliverable is required: HW8.ipynb with your implementation and answers.

You can work in pairs, and each pair only needs to submit one ipython notebook. No report is required, but you should write up answers to the open ended questions as text on the notebook.

Grading Rubric

This assignment is worth 100 points in total, which will be scaled down to be worth the same as your other homeworks. Sections 2.7 and 3.1-3.2 of the homework are extra credit. You can earn up to 60 points of extra credit (see the notebook for details).