Course Info

URB101: Statistics for Social Change

Tuesday/Thursday 2:30-4:10PM

Instructor: Noah Wistman

Email: NOAH.WISTMAN24@gc.cuny.edu  |  noahwistman@gmail.com

Office Hours: Tuesday 4:15-5:15, and by appointment

Course Plan

I want to give you the freedom to learn about what you care about. Therefore, our course has an open design, where you’ll take responsibility for structuring your learning. I also want us to learn from each other. Therefore, our course will involve interactions with your classmates and the work they’re doing.

Course Page

All materials and assignments will be hosted on our Manifold page. Manifold is CUNY’s Open Educational Resource platform. I’m hosting the course here because I want you to be able to see what your classmates are doing, and publish the work you do for this course.

Since Manifold is an open platform, assume that anything you put here is public and could be viewed by anyone. If you want to do a project that’s more personal, let me know and I’ll set up a second space, where you can control who sees what you’re doing.

Grading

Learning is about more than what you do in school or this course. Your grade is only a reflection of how much credit I can give you for what you’ve done in this class, it isn’t a reflection of your overall learning, or value as a person. Therefore, this course will feature a negotiated grading format, where we’ll decide your final grade together.

To do this, I will email you every two weeks with an update about what I’ve seen you accomplish in the class, and the grade I would give you as a result. I’ll ask you to respond to me saying if you think this is fair, and if not, to explain what you’ve done that you feel like I’m not giving you enough credit for. Expect me to be stingy up front, but open to change. In general, I like to see people genuinely investing themselves into what they’re doing, and supporting others.

I give a lot of different options for how to get course credit, so you can pick the options that are interesting to you. There are two main types of in-class assignments, and two main types of homework assignments. I’ll describe them briefly here- see the specific sections on the course page for more details.

In-Class

Classwork

Every class, I’ll have activities planned for us to do together. Possible activities include discussions, presentations, annotating texts, interviews, surveys, and making graphs. Importantly, we’ll be looking at each other’s work, and giving feedback.

Core Assignments

In the course, only these assignments are required and due by certain times. They all have to do with planning and preparing for your projects and final presentation. We’ll start these assignments in-class, and I’ll ask you to add to them at home if they aren’t finished in-class.

Homework

Projects

If you like to learn through experiences, these are the homework options for you! You can work on projects on your own, or with your classmates. Options include doing interviews, handing out surveys, setting personal goals, coding, data analysis, and textual analysis. See the course page for more details about each option.

Research

If you like to learn through sources like books, articles and videos, these are the homework options for you! You can either study on your own, or with your classmates. Options include starting a podcast, providing peer support, presenting in class, finding and reading research, and responding to statistics-related content.

Of course, if you want to do more than one type of assignment, or mix-and-match aspects of different assignments, that will work just fine. And if you don’t like any of the options that are presented on the course page, you can also come up with your own idea and bring it to me. Somehow, we’ll make whatever you think of work.

In general, if you attend every class, do a good job on at least one of the major homework assignments, and do well on the final, you’ll get an A.

Schedule

We have thirty class sessions scheduled for this course. I’ve left some classes open so we have flexibility. I’ll announce any schedule changes during the semester as they come up.

Class 1 - Introduction

Class 2 - Overview

Class 3 - Distribution Plot and Scatter Plot

Class 4 - Statistics Can be Simple

Class 5 - Data Collection

Class 6 - Sampling Bias

Class 7 - Central Tendency

Class 8 - Variation

Class 9 - Sums of Squares, Standard Deviation

Class 10 - Distribution

Class 11 - Probability Distribution

Class 12 - Review

Class 13 - Random Variation and Confidence

Class 14 - Standard Error and Standard Error of the Mean

Class 15 - Statistical Test Equations

Class 16 - Linear Regression

Class 17 - Reporting Statistics

Class 18 - How to Lie With Statistics

Class 19 -  Interpretation

Class 20 - Decision-Making

Class 21 - 27 - Left open

Class 28 - Review

Class 29 - Final Presentation Practice

Class 30 - Final Presentations

Other possible class topics:

Null Hypothesis Significance Testing, The ANOVA, Adjustments, Statistics Software, Meta-Analysis, Mediators, Moderators, Confounds, Norming, Bayesian, Bootstrapping, Data Cleaning, My Own Research