Quantitative Methods 2 (QM2), 56:824:709; cross listed with prevention science Spring 2024; Mon 6-8.50, ATG101

philosophy

Do talk to me about challenges at the beginning! I can accomodate much of it, if you tell me early. Don't wait till the end of the course! Material is cumulative, if you fall behind, it may be fatal.

Not much wiggle room as in other classes: a core required class that will be tested again in qualifying exam. Still, everyone is different (also in this class), and I will try to accomodate that. While there is only one way to excel (learn the material), there is opportunity for extra credit. You can do (extra) math, (extra) statistical programing, civic engagement, having great research ideas and paper. Try to produce a publishable paper.

overview

Class is about Ordinary Least Squares (OLS) regression, with social science focus. This class uses Stata: regression cannot be learnt in an applied way without some use of software.
We will also cover some research design approaches like Difference in Difference models.

student learning objectives/outcomes

pre-requisites

QM1 or the equivalent knowledge. You are expected to be familiar with basic descriptive and inferential statistics. Do not need any knowledge of regression.

communication

Everything is linked from online syllabus (this page). Canvas is only used for discussions/forum and as assignment dropbox.

required textbooks

none

recommended course materials

Mastering Metrics by Angrist and Pischke, especially for more advanced topics/causality, can buy used for about $20 on amzn there are dofiles (not complete!) and data: masteringmetrics.com/resources

note: metrics is somewhat tedious/dull and boring like economics

Basic Econometrics by Gujarati 4th ed used on amzn about 15$. Do not buy older editions than 4. note: Gujarati is full of boilerplate and unnecessary stuff and way too many details; so don't read it too much and skim through

free ucla webbook applied, hands-on using Stata; and 101 regression princeton slides

software

We will use Stata 18. Stata is in the classroom, the Library, and online virtual lab: https://it.rutgers.edu/virtual-computer-labs

You can buy your own Stata with perpetual license for about $200 https://www.stata.com/order/new/edu/profplus/student-pricing/

If you use Python or R no need for Stata (I just use it in class).

calculator

A hand calculator is necessary for midterm. It does not have to be fancy, just the most basic functions. It's about $10.

requirements

problem sets: To learn the material work on problems that reinforce the material. Late problem sets are not accepted (except documented emergency eg hospitalization). Can work in groups but must be separately written.
tests: Open-book, open-note midterm. Calculator is necessary. Laptops/phones/etc not allowed.
paper: Use tools from the class to produce a paper no longer than 10 pages single-spaced. Can have a more typical journal article length, say 10-15 single spaced pages, especially if you have already done some work on a topic and continue in this class (recommended). But please do contact me as early as possible. Can co-author in groups of upto 3 people: group submits one paper (and presentation). (But has to be up to 3x better).

grading

min max grade
90.0100.0A
85.089.9B+
80.084.9B
75.079.9C+
70.074.9C
069.9F

academic calendar

tentative, most uptodate online; i work on these materials continously and they will be changing slightly; university calendar; print several slides on one sheet, say 6; or just annotate electronic copy
[*] = bonus (extra/not required)

jan22 intro/overview vid old vid

jan29 bivariate regression ([*]lab:5.30!) vid old vid

feb5 bivariate regression and basic measurment (stata lab:5.30) vid old vid

feb12 multiple regression, lovb, and advanced measurement (logs; quadratics) (stata lab 5:30) vid old vid

feb19 F-tests, dummies, interactions (5.30 stata lab) vid old vid old vid

feb26 first-half summary vid old vid

mar4 open book open note midterm, bring calculator and t and F tables!

mar11 spring break

applied part of the class: working on your own projects: regressions using data

mar18 final project; q \& a vid old vid old vid

mar25 continue with final project from last week; flip the class work on ps4 vid

apr1 ps4 presentations: no need for ppt; focus on regression results; 5min sharp (i will cut you off) + 5min discussion vid

apr8 violations (heteroskedasticity, model diag) and logit (binary DV)vid [old vid]

apr15 causality1 vid

apr22 causality2 vid

apr29 student presentations and wrap up and review vid

[old vid] presentation tips: for 5 min presentation do not need too much of an outline; do not be shy, publish your research; use pictures, use maps, tell a story, do not overwhelm user, present most important key results, not everything!! be interesting; but have well thought regression results!! this is regression class: need regression results

final paper due: may6 (6p)

marketing: take in fall gis class

rules

do not share or link to class videos! These videocasts and podcasts are the exclusive copyrighted property of Rutgers University and the Professor teaching the course. Rutgers University and the Professor grant you a license only to replay them for your own personal use during the course. Sharing them with others (including other students), reproducing, distributing, or posting any part of them elsewhere -- including but not limited to any internet site -- will be treated as a copyright violation and an offense against the honesty provisions of the Code of Student Conduct.

doing research with humans and other animals If you use data collected by someone else, you are fine. If you collect your own data, do experiments, or in any way do anything with human subjects or other animals, see https://eirb.rutgers.edu

confidential data If you have, handle, or plan to use or collect anyy data that is in any way confidential, eg: SSN, DOB, phone\#, address, name, etc: talk to me first!

attendance Attendance is recommended. You are responsible for any material covered in the class, whether or not it was in the readings or lecture notes. You are also responsible for any announcements made in class. For most students, attendance is simply essential to learning the material. If you do need to miss a class, be sure to consult with a fellow student to learn what transpired.

incompletes The material is best learned as a single unit. Incompletes given only in cases where a substantial change in life circumstances occurs that is beyond the control of the student, and only with documentation.

study groups Very helpful! You're also encouraged to work on problem sets and final project together. However, each student must write up her own answers, based on her own understanding of the material. Do not hand in a copy of another person's problem set, even a member of your own group. Writing up your own answer helps you to internalize the group discussions and is a crucial step in the learning process. Also, if worked in group, spell out group members' names next to your name. You can also submit the same presentation and paper in a group of upto 3 people. So your group would hand in one presentation and paper, but everyone would hand in her own problem set that must differ from others [except problem sets that are drafts of final project; essp the later ones].

academic integrity I am very serious about this. Make no mistake--I may appear accommodating and informal--but I am extremely strict about academic integrity. Violations of academic integrity include cheating on tests or handing in assignments that do not reflect your own work and/or the work of a study group in which you actively participated. Handing in your own work that was performed not for this class (e.g. other class, any other project) is cheating, too. I have a policy of zero tolerance for cheating. Violations are always referred to the university authorities.

For more information see http://fas.camden.rutgers.edu/student-experience/academic-integrity-policy

accommodating students with disabilities Any student with a disability affecting performance in the class should contact the disability office ASAP: https://success.camden.rutgers.edu/success-services/disability-services/

civic engagement component

typical civic engagement

Universities and social science should serve society. This idea will be enforced in this class through graded civic engagement. You will have to engage with local community.

The idea is that you engage civically using data. There are several ways to do it. Ideally, you will partner with a local organization, obtain data from them and present results to them. You may also use government data, say from census bureau, and present relevant information to locals. A local organization can be Rutgers research institute such as WRI, CURE, LEAP or any other organization such as school or soup kitchen or CamConnect-Rutgers Office of civic engagement will help you contact them. The key idea is partnership: you will use tools from this class to produce output useful to local community. This is similar to taking a role of an apprentice at a local organization or serving as a consultant.

Details will follow in specific assignments. Using real world data poses challenges, which is a part of exercise. Presenting your findings to stakeholders outside of a class is also challenging. At the same time, it is fairly easy to contribute locally by using simple tools learned in this class. For instance, simple comparison of means between two schools in Camden can be revealing and helpful locally.

An obvious way would be to use data at your workplace or at a workplace of someone you know. However, you need to make sure that it serves society in some way. For instance, it would be straightforward if you work at a hospital or school or fire department; but it would be difficult if you work at Starbucks.

There will be two or three civic engagement ps and paper has a civic engagement part: you will probably need to spend estimated 30-50 hours total this semester on these assignments outside of the class.

atypical civic engagement

Successful completion of atypical civic engagement will take estimated at least double of the typical civic engagement time.

An apparently straightforward solution is to engage with international academic community by producing research, but this is a good idea only if you can produce an innovative research, which is difficult (but possible). To do this successfully, you'd need to be very sophisticated at academic research. It is easier to contribute locally (traditional civic engagement) than internationally.

Somewhat easier would be engagement at regional or State level-for instance, you may evaluate some policy in NJ as compared to NY, or produce descriptive statistics of a region that would be useful regionally (e.g. my South Jersey WRI presentation). Again, this type of engagement typically requires substantial research experience typically found at late stage of PhD program. There may also be some other atypical ways-let me know your ideas.