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Government Advances in Statistical Programming (GASP) 2020
Government Advances in Statistical Programming (GASP) 2020
November 6th , 2020 9:00 am- 6:00 pm Eastern Daylight Time (EDT)
November 6th , 2020 9:00 am- 6:00 pm Eastern Daylight Time (EDT)
Register in advance for this webinar:
https://nsf.zoomgov.com/webinar/register/WN_Nfc8kaeNR4ur5jl5i-2GnA
About this online event:
About this online event:
A workshop focused on statistical programming for government applications across government and the private sector.
Themes will include R and Python applications, data science, big data and official statistics, open source software, statistical computing software, and more.
Themes will include:
Using R to Streamline analysis
Using statistical software for model selection/validation
Using Python libraries for text analysis and to streamline production
Using R to automate and increase office efficiency
Using Dashboards for data analysis and production
Open source software to increase speed to get more information
Applications of Python and other software for production
Using R shiny and other open source software for analysis of survey data-public use files
Data science
Big data
Official statistics
Version controls and reproducibility
Process automation
DataOps/ DevOps
Presentation involving Data visualization
Natural language processing,
Julia language applications for open-government
Neural networks
PAST GASP Workshops (2018, 2019)
PAST GASP Workshops (2018, 2019)
Last year's GASP workshop was a success. Click here to see past presentations.
Past programs:
GASP 2019 program . GASP 2018 program.
Registration:
Registration:
Registration is free. To register for this event click this Eventbrite link: https://www.eventbrite.com/e/government-advances-statistical-programming-gasp-2020online-tickets-119945047867
Organizers:
Mike Jadoo - datamike8@gmail.com
Lisa Frehill
Francisco Moris
Peter Meyer
Brandon Kopp
Gwynn Sturdevant
Sponsors:
Sponsors:
NSCF National Science Foundation
NSCF National Science Foundation
The National Science Foundation (NSF) is an independent federal agency created by Congress in 1950 "to promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense..." NSF is vital because we support basic research and people to create knowledge that transforms the future. This type of support:
Is a primary driver of the U.S. economy.
Enhances the nation's security.
Advances knowledge to sustain global leadership.
Federal Committee Statistical Methodology (FCSM )Interest Group on Computational Statistics and the Production of Official Statistics (CSPOS)
Federal Committee Statistical Methodology (FCSM )Interest Group on Computational Statistics and the Production of Official Statistics (CSPOS)
The purpose of this interest group is to share information on computational statistics and the production of official statistics across federal agencies, to identify areas of common research, to coordinate collaborative research projects in those areas, and to disseminate information related to computational statistical methods and the implementation of these methods to produce official statistics.
Inter-agency R users group
Inter-agency R users group
This is a government wide group for everybody interested in the R programming language for statistical computing, data science, visualization and reproducible reporting within the context of the discovery and/or streamlining processes. We promote knowledge sharing and the use of open source tools across the different agency’s in government. Whether you are just learning R for the first time or are an expert R user, all are welcome.
Washington Statistical Society
Washington Statistical Society
The WSS is one of the largest chapters of the American Statistical Association (ASA) and extremely active with over 900 members from government, academia and the private sector. WSS offers opportunities to learn through seminars and workshops, and continuing your own statistical education. As well as, socializing through networking with colleagues, and engage in service by increasing the level of quantitative literacy in area schools, and motivating and developing the next generation of statisticians.
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