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        "description":"Be a part of QMSS's first-ever hackathon! A hackathon is a fantastic opportunity to practice your data cleaning, data analysis, data visualization, and data interpretation skills & leave with a data analysis project that you can post about on a professional website, write about on your resumes, and talk about during job interviews as an example of what you know how to do.\r\n\r\nQMSS\u2019s inaugural Hackathon is designed to be accessible to various skill levels in data science and statistics from QMSS courses and beyond.\r\n\r\nStudents will work collaboratively with real, relevant, and timely social science datasets on projects that match up with your skillset, and with no pressure! This is not a competition - it\u2019s a skills development & applied practice opportunity! QMSS Peer Mentors and faculty will be there to help as needed.\r\n\r\nSkills from QMSS 201, 295, and\/or 395 will be sufficient to fully participate in the hackathon -- including students CURRENTLY taking those courses!\r\nStudents with more advanced skills from QMSS 301 and\/or other data science and statistics courses will also be able to flex their data muscles & gain valuable experience from this event.\r\n\r\nCompletion certificates will be given to all students who fully participate to add to your resume, CV, and LinkedIn profiles, and you will also get unique QMSS swag if you RSVP in time! We will provide food throughout the hackathon to keep you fueled & follow up with a social event to celebrate at the end - more details about that to follow!\r\n\r\nA laptop is required for this event - please let us know at qmss.program@umich.edu if you need access to one in order to participate in the event!",
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        "combined_title":"Selective Memory Equilibrium: Drew Fudenberg, Massachusetts Institute of Technology",
        "event_subtitle":"Drew Fudenberg, Massachusetts Institute of Technology",
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        "description":"People often have imperfect memory and only remember some of their past experiences, and their memory can be selective, in that they are more likely to remember some events than others. Moreover, their mem- ory is stochastic. \"Selective Memory Equilibrium\" considers a selective memory model where the number of recalled experiences goes to infinity as the agent\u2019s sample size increases, and agents are unaware of their selective memory, so they update their beliefs as if the experiences they remember are the only ones that occurred.\"Learning and Limited Memory\"  considers a similar model, except that the expected number of instances recalled by the agent remains bounded as their number of past experiences goes to infinity  It also  experiences that were remembered in one period to be more likely to be recalled in the next one.\r\n\r\nThis talk is presented by the Economic Theory Seminar, sponsored by the Department of Economics with generous gifts given through the Mark Harms Fund and the Economics Strategic Fund.",
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