1. Description
2. Learning Outcomes
3. Logistics
4. Marking Scheme
5. Policies
6. Folder Structure
7. Acknowledgements and Contributions

The goal of this module is to introduce the essentials of sampling, probability, and survey methodology. This includes simple probability samples, stratified sampling, cluster sampling, dealing with non-response, estimating and survey quality. Students will consider the theoretical foundations of different sampling approaches, as well as practical applications of this knowledge towards contexts such as market research, political polling, and the Canadian census. Analysis using the Python programming language will also be highlighted, drawing on skills developed in previous modules.

1. Develop ability to implement simple probability samples.
2. Understand more complicated sampling procedures and the tradeoffs involved.
3. Identify and understand sources of error or inaccuracies in data as a result of sampling strategies.
4. Develop intuition around survey quality.

• Instructor: [Ciara Zogheib]. [email protected]
• Instructor: [Alex Yu]. [email protected]
  • Email etiquette: Emails are welcomed. Please copy both instructors if emailing. We will try to respond within 48-hours.

The course will be held online, four days a week. Each day will be 2.5 hours. Being mindful of online fatigue, there will be one break during each class where students are encouraged to stretch, grab a drink and snacks, or ask any additional questions.

Camera is optional although highly encouraged. We understand that not everyone may have the space at home to have the camera on.

• Monday March 25 6:00-8:30 PM (Course Overview, Sampling Basics)
• Tuesday March 26 6:00-8:30 PM (Probability 101)
• Wednesday March 27 6:00-8:30 PM (Populations and Samples)
• Thursday March 28 6:00-8:30 PM (Types of Sampling)
• Tuesday April 2 6:00-8:30 PM (Types of Sampling (continued))
• Wednesday April 3 6:00-8:30 PM (Errors in Sampling)
• Thursday April 4 6:00-8:30 PM (Survey Quality and Questionnaire Design)
• Saturday April 6 9:00-11:30 AM (Sampling Ethics)
• Monday April 8 ASYNCHRONOUS CLASS (Survey Quality Continued))
• Tuesday April 9 6:00-8:30 PM (Sampling Practice)
• Thursday April 11 6:00-8:30 PM (Guest Speaker)

Rubrics for each assignment (pass/fail) are included in each assignment document in the 'assessments' folder. Please submit your assignments using your existing google folders.

Questions are encouraged! Extensions for assessments may be granted but the hard deadline for all assessments is April 11, 2024. Please ask for extensions as soon as possible.

Submissions can be submitted late on an as needed basis. The hard deadline for all assessments, however, is April 11, 2024. No assessment will be graded past this date.

We will indicate when assignments can be collaborative vs. individual. For individual assignments, please write your own solutions. If you use any outside resources, please cite them. Using large language models is discouraged but allowed. We have found that using answers from these are variable at best. Please use your best judgment.

Below are the folders contained in this repo with a description of what they contain and information on how to use them.

This folder contains the assessments for the workshop. Assignments will be discussed in detail in class.

This folder contains the powerpoint files for the slides.

This folder contains additional resources that can help students throughout the workshop, as content is cumulative. Unfortunately, there is not enough time to review previous content each class so while these exercises are not graded, they are highly recommended.

These were used to plan the course but we are not following them exactly so feel free to ignore.

Radu Craiu, and the Department of Statistical Sciences, suggested this course. Rohan Alexander managed its development. Annie Collins developed the materials intially.