Experimental Design and Causal Inference
QAC 307
Fall 2018
| Section:
01
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| Crosslisting:
CIS 307 |
| Course Cluster: Data Analysis Minor |
The course provides the foundations and statistical thinking to design, collect, and analyze experimental data and introduces appropriate techniques for observational data when causal inference is the objective of the analysis. Throughout the course, we introduce and compare various experimental designs. We will discuss sample size and power calculations as well as the advantages and disadvantages of each of these designs. With observational data, we will explore difference-in-difference models, propensity score matching techniques, regression discontinuity designs. This course gives students the opportunity to develop further their computational skills as we learn how to describe, interpret, control, and draw inferences from experimental and observational data. |
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| Credit: 1 |
Gen Ed Area Dept:
NSM QAC, SBS QAC |
| Course Format: Lecture / Discussion | Grading Mode: Graded |
| Level: UGRD |
Prerequisites: QAC201 OR PSYC200 OR MATH132 OR ECON300 |
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Fulfills a Requirement for: (CADS)(DATA-MN)(IDEA-COMP)(PSYC) |
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Past Enrollment Probability: 75% - 89% |
| SECTION 01 | | Special Attributes: CQC |
Major Readings: Wesleyan RJ Julia Bookstore
Van Belle, G. and Kerr, K. DESIGN AND ANALYSIS OF EXPERIMENTS IN THE HEALTH SCIENCES, (accessible online through Wesleyan library)
Morgan, S. and Winship, C. COUNTERFACTUALS AND CAUSAL INFERENCE: METHODS AND PRINCIPLES OF SOCIAL RESEARCH
Shadish, Cook, Campbell, EXPERIMENTAL AND QUASI-EXPERIMENTAL DESIGNS FOR GENERALIZED CAUSAL INFERENCE
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Examinations and Assignments:
This course will have several homework assignments, a midterm, and a semester-long course project, which will involve designing, implementing, and analyzing an experiment. Part of the grade will be based on class participation and preparedness. |
Additional Requirements and/or Comments:
The course includes extensive lab work/exercises with statistical computing tools.
An introductory statistics/applied data analysis background (familiarity with multivariate regression) is a prerequisite for the course and that is why QAC201, or ECON 300, etc. are listed as formal prerequisites. The course instructor will approve Pre-req overrides for students who satisfy the basic requirements through other course work. |
| Instructor(s): Nazzaro,Valerie L. Times: ..T.R.. 10:20AM-11:40AM; Location: ALLB204; |
| Total Enrollment Limit: 19 | | SR major: 0 | JR major: 0 | | |
| Seats Available: 0 | GRAD: 2 | SR non-major: 7 | JR non-major: 7 | SO: 3 | FR: 0 |
| Drop/Add Enrollment Requests | | | | | |
| Total Submitted Requests: 1 | 1st Ranked: 1 | 2nd Ranked: 0 | 3rd Ranked: 0 | 4th Ranked: 0 | Unranked: 0 |
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