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        "event_title":"Online Arabic Placement test_June 10, 2025 (12pm-3pm EST)",
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        "combined_title":"Online Arabic Placement test_June 10, 2025 (12pm-3pm EST)",
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        "event_type":"Workshop \/ Seminar",
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        "description":"Welcome to the Arabic Placement TestAbout the testThe test takes approximately two hours and a half in length, and it is composed of three portions:a. The writing portion is completed via Zoom and it is worth a total of 100 points.b. The reading portion is completed online through Canvas site, and it is worth a total of 48 points.c. Right after finishing with the reading portion, each student will have a follow-up interview with a proctor. The interviews last approximately 15 minutes and it is worth a total of 20 points.Important: The interview portion will be weighted most heavily as it will be used to validate performance on the other two portions. The final result\/score\/rating will thus be based on the student\u2019s performance on the interview above all. Rating of performance on the writing or reading portions is secondary.\nHow is the result calculated?Students who receive 60% or above will be placed in Arabic 401 and thus placed out of the\u00a0LSA Language Requirement.Where can I view my results?\u00a0Placement results are posted within 7 business days after taking the test. You will not be notified of your score automatically.\u00a0You may view your placements via: Wolverine Access > Student Business > Academic Records > View Placement Exam Results.\nImportant information about the test* Please note that only students who are participating in the Spring\/Summer orientations are eligible to take the online placement test. If you are an existing UM student, please sign up to take the in-person placement test that is taking place in August.* Placements are valid for only one year. If you fail to register in the course that you are placed in, you will be required to retake the test.* Retaking the placement test is only permitted after the placement results expire.* Students who are currently taking an Arabic course will not be allowed to take the placement test.\u00a0* The test assesses students\u2019 proficiency in Standard Arabic (fuSHa), NOT colloquial Arabic.* If you speak an Arabic dialect but you do not know how to read or write or have little knowledge, feel free to register in Arabic 101.* Students who know some Arabic because they came from an Arabic-speaking household or have studied Arabic before, must take the Arabic proficiency test in order to determine their placement.* Students who have taken Arabic at other institutions and wish to continue their Arabic study at UM must take the placement test to determine their level. Credits for Arabic study undertaken at another institution prior to joining UM or in a summer program while attending UM, transfer in as generic departmental credits and students must take the placement test to determine credit equivalencies to UM courses.* If you place in or beyond the 401 level, you will have satisfied the LSA language requirement.* Students are encouraged to take a placement test as early as possible in their studies in order to determine the level they should enroll in, or if they test out of the language requirement. This is extremely important to avoid delays in graduation and complications with placement.* Arabic 101, 201, 401, 501 or 504 are offered ONLY in the Fall semester, and Arabic 102, 202, 402, 511 are ONLY offered in the Winter semester.* Arabic 103 (the equivalent of Arabic 101 & 102, combined) AND Arabic 203 (the equivalent of Arabic 201 & 202, combined) are offered in the Spring-Summer terms.UM\u2019s Arabic curriculum is a dual register curriculum in which students learn to speak and understand the Levantine dialect (the dialect of Jordan, Syria, Palestine and Lebanon) in addition to developing the four language skills of formal Arabic (fuSHa).\u00a0If you have questions regarding the placement test, please contact the Arabic program director at, mesarabicprogram@umich.edu",
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        "event_title":"Summer Institute Course - Designing and Writing Questions for Surveys: Guidelines and Recommendations",
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        "combined_title":"Summer Institute Course - Designing and Writing Questions for Surveys: Guidelines and Recommendations: Presented by Jennifer (Jen) Dykema",
        "event_subtitle":"Presented by Jennifer (Jen) Dykema",
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        "description":"Designing and Writing Questions for Surveys: Guidelines and Recommendations\r\nJune 9-13, 2025\r\n1:00pm-4:00pm EDT\r\nLive Online via Zoom\r\n\r\nCourse Objectives\r\n\u2022 Introduce a structural analysis of parts of a survey question\r\n\u2022 Introduce cognitive interviewing as a method for testing survey questions\r\n\u2022 Describe guidelines for diagnosing problems in survey questions and writing new survey questions\r\n\u2022 Focus on the structure and wording of survey questions, whether for interviewer-administered or self- administered instruments\r\n\u2022 Provide an opportunity to apply the guidelines and principles during in-class exercises\r\n\u2022 Focus on improving individual questions and sets of questions.\r\n\u2022 Summarize research that underlies key decisions in writing survey questions.\r\n\r\nDescription\r\nThis workshop distills research about survey questions to principles that can be applied to write survey questions that are clear and obtain reliable answers. The workshop provides students with tools to use in diagnosing problems in survey questions and in writing their own survey questions. Sessions combine lecture with group exercises and discussion. The lecture provides guidelines for writing and revising survey questions and illustrates how to revise troubled questions. Assignments require that students analyze problematic questions, revise them, and administer them to fellow students. Sessions consider both questions about events and behaviors and questions about subjective phenomena (such as attitudes, evaluations, and internal\r\nstates).\r\n\r\nWho Should attend\r\nIndividuals who will be writing or reviewing survey questions or survey instruments or analyzing survey data. This course gives practical guidance to those who have written survey questions but who are not familiar with research on question design, those who are just beginning to design survey instruments, and those who use survey data but do not themselves design survey instruments.\r\n\r\nThe Summer Institute in Survey Research Techniques provides rigorous and high quality graduate level training in all phases of survey research. The noncredit courses are open to all. The courses are live online via Zoom. Registration and payment are required. Course fees are based on the total number of hours assigned to each course, the hours are listed on the course description. The 2025 schedule lists additional courses. If you have any questions regarding the application process, please use the online contact form or email the Summer Institute at isr-summer@umich.edu .\r\n\r\nThe program teaches state-of-the-art practice and theory in the design, implementation, and analysis of surveys. The Summer Institute in Survey Research Techniques has presented courses on the sample survey since the summer of 1948, and has offered such courses every summer since. The Summer Institute uses the sample survey as the basic instrument for the scientific measurement of human activity. It presents sample survey methods in courses designed to meet the educational needs of those",
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        "tags":["Data","Data Analysis","Data Collection","Data Curation","Data Linkage","Data Management","Data Science","Survey Methodology","Survey Methods","Survey Research"],
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        "event_title":"Understanding and Managing ADHD: Free Parent & Guardian Workshop",
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        "description":"This free virtual workshop is designed to help parents or guardians. Your child may have received a formal diagnosis already, or you may suspect they have ADHD or a similar learning challenge. Participants learn more about what ADHD is, what it \u201clooks\u201d like in children, how it differs from what you might expect\/how it is presented in media, and where to go from here.\r\n\r\nParticipants can expect to learn:\r\n+ What causes ADHD.\r\n+ What ADHD looks like in children.\r\n+ How to support a child with ADHD at home, school, and with friends.\r\n\r\nThis workshop includes interactive components and a Question-and-Answer session at the end. To help us better prepare and tailor the content of each workshop, we ask participants to provide their most pressing questions in writing when they register.",
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        "event_title":"Mechanistic Modeling of Complex Health Problems with Deep Learning",
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        "combined_title":"Mechanistic Modeling of Complex Health Problems with Deep Learning: Prayag Chatha",
        "event_subtitle":"Prayag Chatha",
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        "description":"Though they show impressive empirical accuracy, machine learning methodologies have been criticized for not producing interpretable, scientific theories. In both clinical medicine and public health, the researchers aim not just to predict health outcomes, but to improve them. Hence, causal, human-interpretable models of nature hold particular value in these fields. In this dissertation, I investigate how deep learning, when integrated into scientifically-informed models and principled statistical frameworks, can be used to advance mechanistic modeling in the health sciences.\r\n\r\nSince the widespread adoption of electronic health records (EHRs), there has been growing interest in evaluating medical interventions through large-scale observational studies of diverse patient populations. In the first chapter, I examine the opportunities and challenges that arise from applying deep neural networks to EHR data. Despite the vast scale of EHR datasets, black box predictive modeling has limited value for informing clinical care, where human judgment is indispensable. Medical researchers are often interested in estimating counterfactual treatment eff ects on patients\u2019 time-to-event outcomes. In the second chapter, I propose the Dynamic Survival Transformer (DynST), a deep survival model that flexibly estimates hazards from both static and time-varying features typical of EHR data, and demonstrate how DynST supports robust, semiparametric inference for causal survival analysis.\r\n\r\nStochastic infectious disease models capture uncertainty in public health outcomes and off er mechanistic explanations of transmission patterns. However, they are often nonlinear dynamical systems with massive latent state spaces, making likelihood-based inference of model parameters difficult. In the third chapter, I develop a methodology for efficiently calibrating large-scale stochastic epidemic simulation models to observed data using Neural Posterior Estimation. In NPE, a neural network trained on simulated data learns to \u201cinvert\u201d a stochastic simulator and returns a parametric approximation of the posterior distribution. I use NPE to calibrate a stochastic Susceptible-Infected model to a study of a healthcare-associated infection in a long-term acute care hospital and find evidence of spatially heterogeneous patient-to-patient transmission risk.",
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        "event_title":"Reducibility and Anosov Representations",
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        "combined_title":"Reducibility and Anosov Representations: Max Lahn",
        "event_subtitle":"Max Lahn",
        "event_type":"Presentation",
        "event_type_id":"16",
        "description":"Abstract:\r\n\r\nIn this thesis, we explore the framework of Anosov representations for reducible representations of a non-elementary word hyperbolic group. We give characterizations of the Anosov condition for these reducible representations in terms of the eigenvalues of the irreducible block factors of its semisimplification, or more generally, of the block factors of its block diagonalization. In the character variety, these Anosov representations comprise a collection of bounded convex domains in certain finite-dimensional vector spaces, and this perspective allows us to conclude for many non-elementary hyperbolic groups that connected components of the character variety which consist entirely of Anosov representations do not contain reducible representations. Applying these results to reducible suspensions, we obtain explicit examples of non-Anosov limits of reducible Anosov representations.",
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