UED 721 Online fall 2022

This is the main page for UED 721 online at the CUNY Graduate Center, taught by Prof. Wladis. This class is taught entirely online.

Important course links:

  • The syllabus: link to basic syllabus as a pdf here

    This syllabus outlines the general class structure and assignments; however, all of the details about readings and course assignments will be on this webpage.

    Update: Note about Stata: I have finally gotten confirmation from the GC that they have secured a Stata license for students, but they do not have information yet about how to use it. You will not need it right away in the course, so for now, I suggest holding off on purchasing access to Stata, since you should be able to get access free through the GC soon, and I will notify you via email and/or updates here on this page about how to obtain access to the new GC Stata license for students.

  • How to submit your assignments: Assignments for the course will be organized using Google drive. Please create a folder titled "Firstname Lastname UED 721 assignments fall 2022" and share it with me at cwladis@gmail.com. This is where your assignments for the course will go--I will assign grades and comments here as well.

  • Prof Wladis contact info:

    • email: profwladis@gmail.com or cwladis@bmcc.cuny.edu
    • phone extension: 212-220-1363 (email is faster)
    • office hours: TBA, to be posted here by first day of class
  • Class Meetings and Assignments

    This is where all course meetings and assignments will be posted throughout the term.

    Class Meetings

    This class will meet via Zoom roughly every other week throughout the semester (check the email you have listed in CUNYfirst for the link). Between Zoom meetings, the course will be conducted asynchronously online.

    • 8/25/22
    • 9/8/22
    • 9/22/22
    • 10/6/22
    • 10/27/22
    • 11/10/22
    • 12/1/22

    Readings and Assignments

    The actually readings and assignments will be based on student interests during the term. Readings and assignments for the beginning of the term are posted here and will be updated regularly in response to student interests.

    Assignment 0: Tell me about yourself

    For this first assignment (due 9/2/22), please create a google doc inside your shared folder with me for the class (see instructions above), and in roughly one page, tell me about:

    • What your background is in statistics so far (very brief description is fine).
    • How far along you are in your graduate program (not just the year, but when do you anticipate starting some kind of independent research? do you already have a sense of what your dissertation topic might be?).
    • What research questions you are thinking about that might interest you short-term or long-term.
    • What you hope to get out of this class.
    • Anything specific that you would like to learn in this class.
    • Anything about this class that makes you nervous, or that you are uncertain about.
    • Anything else you would like to share.

    First Module: What is linear regression, and how can we use it to make inferences? (aim to discuss at second and third class meetings)

    You may have already learned about linear regression in detail, or you may have had little instruction so far in linear regression. In this course our goal is not to spend a lot of time teaching you nitty gritty details on how to conduct linear regression analysis, but rather to think about what inferences we can make based on various linear regression analyses. This first module is intended to take roughly weeks, but we may adjust the deadline based on our first course meetings together. Your goal should be to finish enough of the assignment that you are ready to ask questions and discuss any difficulties that you have run into during our 9/8/22 class meeting if at all possible. We will discuss this project during that class meeting. Based on how this goes, I will make further decisions about subsequent topics and assignments, as well as set the deadline for this project. Depending on how interests and backgrounds of students vary, we may split into subgroups with some variation in topics and assignments.

    Second Module: Statistical Significance: Use and Misuse (link upcoming)

    In this section we will look at how to calculate and interpret confidence intervals, more generally, and in the context of linear regression. In particular, we will discuss the role of statistical significance in making inferences, including many nuances and pitfalls involved in the use of p-values and confidence intervals.

    Subsequent Topics:

    Based on student background and interest, future topics to be explored may include: mediation and moderation; logistic regression; discussion of when quantifying qualitative data might or might not be appropriate; limitations in real-world data collection and how this might impact the inferences we are able to make; issues of non-response and missing data; etc.