From acmsmajors at u.washington.edu Wed Nov 6 11:33:23 2024 From: acmsmajors at u.washington.edu (Math & ACMS Student Services Office via Acmsmajors) Date: Wed Nov 6 15:59:42 2024 Subject: [Acmsmajors] Y Math? A new lecture series showcasing mathematical career paths In-Reply-To: References: Message-ID: Dear all, A reminder about this talk on Friday - hope you can join us. Best regards, Math & ACMS Advising Department of Mathematics Padelford Hall C-36 Drop-in Advising Hours Math and ACMS Blog math.washington.edu acms.washington.edu [cid:882a0562-0893-4d6c-8d18-b7852efbc59e] ________________________________ From: Math & ACMS Student Services Office Sent: Monday, October 28, 2024 2:11 PM To: mathmajors@uw.edu ; acmsmajors@uw.edu Subject: Y Math? A new lecture series showcasing mathematical career paths [cid:7cd9c111-fa3b-4ce2-9cfa-835db7fb32a9] Best regards, Math & ACMS Advising Department of Mathematics Padelford Hall C-36 Drop-in Advising Hours Math and ACMS Blog math.washington.edu acms.washington.edu [cid:6e711821-8583-42da-9198-6ec34f9d958b] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/jpeg Size: 979086 bytes Desc: image.png URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Outlook-gbob3cye.png Type: image/png Size: 3180 bytes Desc: Outlook-gbob3cye.png URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Outlook-2ee4q1ro.png Type: image/png Size: 3180 bytes Desc: Outlook-2ee4q1ro.png URL: From acmsmajors at u.washington.edu Tue Nov 19 09:38:49 2024 From: acmsmajors at u.washington.edu (Math & ACMS Student Services Office via Acmsmajors) Date: Tue Nov 19 09:40:23 2024 Subject: [Acmsmajors] Fw: ECON 488- open for registration In-Reply-To: References: Message-ID: ECON 488A ? Causal Inference Sln 13897 TTh 8:30-10:20am MUE 155 In this course we study methods for recovering causal relationships in economics. These methods underpin applied research in social and biomedical sciences, and have many applications in industry, tech companies, consulting firms, et cetera. For example, we may want to establish whether: (a) studying economics increases earnings, for a group of undeclared students; (b) a particular pricing strategy increases a firm?s profits; or (c) higher migration helps or hinders the economic outcomes of existing residents. The recent surge of interest in causal inference is exemplified by the award of the 2021 ?Nobel Prize in Economic Sciences? to Joshua Angrist and Guido Imbens for their work on ?the analysis of causal relationships?. Many elements of this course are based on inferential methods that they pioneered. Sample topics include: treatment/control, regression adjustment, matching (exact, nearest-neighbor), difference-in-difference, synthetic controls, instrumental variables, local average treatment effect (LATE), and regression discontinuity design. We may also discuss how machine learning has recently been used to enrich the classical methods. By the end of the course, students will be able to approach problems of causal inference that are routinely considered at public and private research institutions and agencies, economic consulting companies, as well as in major technology companies and retailers. This includes the ability to set up, run, and interpret the findings of the methods learned in class. This course is designed for upper-lever undergraduate, or master-level, students in economics and related fields. Ahna Kotila (she/her) Academic Services Director Department of Economics 314 Savery Hall, Box 353330 Seattle, WA 98195-3330 akotila@uw.edu / https://econ.washington.edu [cid:ii_193457d50ab4cdccc1] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.gif Type: image/gif Size: 1303 bytes Desc: image001.gif URL: