ILRST 3900
Last Updated
- Schedule of Classes - January 11, 2024 7:32PM EST
- Course Catalog - January 11, 2024 7:07PM EST
Classes
ILRST 3900
Course Description
Course information provided by the Courses of Study 2023-2024. Courses of Study 2023-2024 is scheduled to publish mid-June.
Causal claims are essential in both science and policy. Would a new experimental drug improve disease survival? Would a new advertisement cause higher sales? Would a person's income be higher if they finished college? These questions involve counterfactuals: outcomes that would be realized if a treatment were assigned differently. This course will define counterfactuals mathematically, formalize conceptual assumptions that link empirical evidence to causal conclusions, and engage with statistical methods for estimation. Students will enter the course with knowledge of statistical inference: how to assess if a variable is associated with an outcome. Students will emerge from the course with knowledge of causal inference: how to assess whether an intervention to change that input would lead to a change in the outcome.
When Offered Fall.
Prerequisites/Corequisites Prerequisites: STSCI 2110 or PSYCH 2500 or SOC 3010 or ECON 3110 or equivalent.
Regular Academic Session. Choose one lecture and one discussion. Combined with: INFO 3900, STSCI 3900
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Credits and Grading Basis
3 Credits Stdnt Opt(Letter or S/U grades)
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Class Number & Section Details
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Meeting Pattern
- TR Warren Hall 175
- Aug 21 - Dec 4, 2023
Instructors
Lundberg, I
Wang, Y
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Additional Information
Instruction Mode: In Person
Causal claims are essential in both science and policy. Would a new experimental drug improve disease survival? Would a new advertisement cause higher sales? Would a person’s income be higher if they finished college? These questions involve counterfactuals: outcomes that would be realized if a treatment were assigned differently. This course will define counterfactuals mathematically, formalize conceptual assumptions that link empirical evidence to causal conclusions, and engage with statistical methods for estimation. Students will enter the course with knowledge of statistical inference: how to assess if a variable is associated with an outcome. Students will emerge from the course with knowledge of causal inference: how to assess whether an intervention to change that input would lead to a change in the outcome.
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Class Number & Section Details
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Meeting Pattern
- W Olin Hall 145
- Aug 21 - Dec 4, 2023
Instructors
Lundberg, I
Wang, Y
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Additional Information
Instruction Mode: In Person
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Class Number & Section Details
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Meeting Pattern
- W Upson Hall 146
- Aug 21 - Dec 4, 2023
Instructors
Lundberg, I
Wang, Y
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Additional Information
Instruction Mode: In Person
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Class Number & Section Details
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Meeting Pattern
- W Upson Hall 152
- Aug 21 - Dec 4, 2023
Instructors
Lundberg, I
Wang, Y
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Additional Information
Instruction Mode: In Person
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Class Number & Section Details
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Meeting Pattern
- W Warren Hall 137
- Aug 21 - Dec 4, 2023
Instructors
Lundberg, I
-
Additional Information
Instruction Mode: In Person
-
Class Number & Section Details
-
Meeting Pattern
- W Upson Hall 152
- Aug 21 - Dec 4, 2023
Instructors
Lundberg, I
Wang, Y
-
Additional Information
Instruction Mode: In Person
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