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DTSTART;TZID=America/Detroit:20190604T140000
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DTSTAMP:20260607T211100
CREATED:20230905T171401Z
LAST-MODIFIED:20230905T171401Z
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SUMMARY:Multiple testing and large-scale inference in Python
DESCRIPTION:This workshop will cover techniques for conducting large-scale inference\, using Python and its libraries.  We will cover the principals of how large scale inference is different from classical inference\, and why multiple comparisons should usually be accounted for in an analysis.  We will then discuss the Bonferroni method\, Benjamini and Hochberg’s False Discovery Rate (FDR)\, Efron’s local FDR\, the Scheffe approach\, and the knockoff filter.  The motivation for each approach will be covered\, and the process for carrying it out in a data analysis will be discussed in detail.  Several case studies will be used to illustrate these analytic approaches.
URL:https://micde.umich.edu/event/multiple-testing-and-large-scale-inference-in-python/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190607T130000
DTEND;TZID=America/Detroit:20190607T163000
DTSTAMP:20260607T211100
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UID:10000234-1559912400-1559925000@micde.umich.edu
SUMMARY:Advanced batch computing with Slurm on the Great Lakes cluster
DESCRIPTION:OVERVIEW\n\n\nThis workshop will cover some more advanced topics in cluster computing on the U-M Great Lakes Cluster. Topics to be covered include a review of common parallel programming models and basic use of Great Lakes; dependent and array scheduling; troubleshooting and analysis; a brief introduction to workflow scripting using bash; parallel processing in one or more of Python\, R\, and MATLAB; and parallel profiling of C and Fortran code using Allinea Performance Reports and Allinea MAP of one or more of MPI and OpenMP programs. \nPRE-REQUISITES\nThis course assumes familiarity with the Linux command line as might be got from the CSCAR/ARC-TS workshop Introduction to the Linux Command Line. In particular\, participants should understand how files and folders work\, be able to create text files using the nano editor\, be able to create and remove files and folders\, and understand what input and output redirection are and how to use them. \nINSTRUCTORS\nDr. Charles J Antonelli\nResearch Computing Services\nLSA Technology Services \nCharles is a High Performance Computing Consultant in the Research Computing Services group of LSA TS at the University of Michigan\, where he is responsible for high performance computing support and education\, and was an Advocate to the Departments of History and Communications. Prior to this\, he built a parallel data ingestion component of a novel earth science data assimilation system\, a secure packet vault\, and worked on the No. 5 ESS Switch at Bell Labs in the 80s. He has taught courses in operating systems\, distributed file systems\, C++ programming\, security\, and database application design. \nJohn Thiels\nResearch Computing Services\nLSA Technology Services \nMATERIALS\n\nLecture Notes (TBD)\nMPI Profiling with Allinea MAP\nGreat Lakes Slurm HPC cluster\n\n\nCOURSE PREPARATION\nIn order to participate successfully in the workshop exercises\, you must have a Great Lakes user account\, a Great Lakes job account (one is created for each workshop)\, and be enrolled in Duo. The user account allows you to log in to the cluster\, create\, compile\, and test applications\, and prepare jobs for submission. The job account allows you to submit those jobs\, executing the applications in parallel on the cluster and charging their resource use against the account. Duo is required to help authenticate you to the cluster. \nGREAT LAKES USER ACCOUNT\nIf you already have a Flux user account\, you don’t need to do anything to obtain a Great Lakes user account.  Otherwise\, go to the Flux user account application page at: https://arc-ts.umich.edu/fluxform/ . \nPlease note that obtaining a user account requires human processing\, so be sure to do this at least two business days before class begins. \nGREAT LAKES JOB ACCOUNT\nWe create a job account for the workshop so you can run jobs on the cluster during the workshop and for one day after for those who would like additional practice. The workshop job account is quite limited and is intended only to run examples to help you cement the details of job submission and management. If you already have an existing Great Lakes job account\, you can use that\, though if there are any issues with that job account\, we will ask you to use the workshop job account. \nDUO AUTHENTICATION\nDuo two-factor authentication is required to log in to the cluster. When logging in\, you will need to type your UMICH (AKA Level 1) password as well as authenticate through Duo in order to access Great Lakes. \nIf you need to enroll in Duo\, follow the instructions at Enroll a Smartphone or Tablet in Duo. \nPlease enroll in Duo before you come to class. \n\nLAPTOP PREPARATION\nYou do not need to bring your own laptop to class. The classroom contains Windows or Mac computers\, which require your uniqname and UMICH (AKA Level 1) password to login\, and that have all necessary software pre-loaded. \nIf you want to use a laptop for the course\, you are welcome to do so:  please see our web page on Preparing your laptop to use Flux. However\, if there are problems connecting your laptop\, you will be asked to switch to the provided computer for the class. We cannot stop to debug connection issues with personal or departmental laptops during the class. \n\nIf you are unable to attend the presentation in person we will be offering a link into the live course via BlueJeans. Please register as if attending in person.  This will put you on the wait list but we will get your account setup for remote attendance.
URL:https://micde.umich.edu/event/advanced-batch-computing-with-slurm-on-the-great-lakes-cluster/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
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DTSTART;TZID=America/Detroit:20190620T150000
DTEND;TZID=America/Detroit:20190620T163000
DTSTAMP:20260607T211100
CREATED:20230905T171401Z
LAST-MODIFIED:20230905T171401Z
UID:10000235-1561042800-1561048200@micde.umich.edu
SUMMARY:R package demo: gganimate and patchwork
DESCRIPTION:This brief workshop will demonstrate the capabilities of two recent R packages\, gganimate and patchwork. One package allows the data explorer to provide some lively enhancement to an otherwise static plot\, without doing much more than standard plots with ggplot2. Likewise\, the other package can seamlessly combine multiple ggplots of varying kinds into one cohesive visualization. \nPrior knowledge of ggplot2 is required\, but not much else. Note also that this is just a demo. No statistical or analytical concepts will be discussed\, and while participation is certainly welcomed\, one can simply watch the demonstration.
URL:https://micde.umich.edu/event/r-package-demo-gganimate-and-patchwork/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190621T093000
DTEND;TZID=America/Detroit:20190621T160000
DTSTAMP:20260607T211100
CREATED:20230905T171402Z
LAST-MODIFIED:20230905T171402Z
UID:10000078-1561109400-1561132800@micde.umich.edu
SUMMARY:Introduction to Stata
DESCRIPTION:Topics: \n\nBy the end of the workshop\, participants will be able to:\n\nWork with Stata\, including using Do-files and using the help system.\nGet data into Stata and manage your data files\nEstablish familiarity with your data\nClean the data to prepare it for analysis\nCheck for basic errors in the data\nGenerate new variables or manipulate existing variables\nMerge or reshape the data.\nProduce summary tables and descriptive statistics.\n\n\nNote: This is a full day workshop. To get the most out of it\, please plan to stay for the entire class.\n\n(Topics subject to change) \nIf you have questions about this workshop\, please send an email to jerrick@umich.edu
URL:https://micde.umich.edu/event/introduction-to-stata-3-3-2-2-2/
LOCATION:Modern Languages Building (MLB)\, Room 2001A
CATEGORIES:Workshops
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DTSTART;TZID=America/Detroit:20190628T130000
DTEND;TZID=America/Detroit:20190628T160000
DTSTAMP:20260607T211100
CREATED:20230905T171402Z
LAST-MODIFIED:20230905T171402Z
UID:10000226-1561726800-1561737600@micde.umich.edu
SUMMARY:Modeling spatially correlated data
DESCRIPTION:This workshop will cover introductory concepts\, tools\, and techniques to model spatially referenced data observed over a regular or irregular grid. We will cover models such as spatial autoregressive that emphasizes the idea of spatial correlation via neighborhood. \nThe workshop will focus on conceptual aspects\, diagnostics tests\, implementation in R\, and interpretation of results.
URL:https://micde.umich.edu/event/modeling-spatially-correlated-data/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
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