Discussion: View Thread

The Section on Statistical Computing of the ASA is excited to host its online symposium (asa-ssc.github.io/minisymp2023) on Saturday, November 4, 2023.  The symposium, "Statistical Computing in Action", aims to demonstrate the remarkable potential and elegance of statistical computing and provide a platform to refine statistical computing expertise, enriching skill sets and problem-solving capabilities.  Additionally, the event endeavors to foster a collaborative and inclusive community that bridges the gap across various computing languages, encouraging knowledge exchange and mutual growth.

Registration and abstract submission are now open.  Please visit the website:  https://asa-ssc.github.io/minisymp2023

The program includes:

+ Keynote address by Simon Urbanek (Executive Editor of R Journal and Senior Lecturer of Data Science at University of Auckland).
+ Data Jamboree in which experts in Julia, Python, and R attack a data analysis in their respective languages.
    - Julia: HaiYing Wang (University of Connecticut)
    - Python: Shannon Taas, (Brigham Young University)
    - R: Lucy D'Agostino McGowan (Wake Forest University)
+ Lightning session with contributed talks from the community... That's you!
+ Panel discussion on open-source software, open data, and open computing featuring
    - Tracy Teal (Open Source Program Director at Posit)
    - Carol Willing (Python and Jupyter Core Developer, VP of Engineering at Noteable)
    - Achim Zeileis (Editor-in-Chief of Journal of Statistical Software, Professor at Universität Innsbruck)

The event is very cheap (as cheap as "free" for all student members of the Statistical Computing Section). We kindly request you to spread the word and share this opportunity with anyone who may have an interest in statistical computing and data science.

Please contact the committee with any questions.

Sincerely,

David Dahl (co-chair), Brigham Young University
Kun Chen (co-chair), University of Connecticut
Mingzhao Hu, Mayo Clinic
Jun Yan, University of Connecticut

Hi, Jun Yan,

We submitted online per instructions.  I'm want to make sure that you get the below. 

Title:

Rule-Based Data Validation and Reconciliation of Survey Responses

Abstract

Each year the US Department of Agriculture's National Agricultural Statistics Service (NASS) conducts more than a hundred surveys to understand and enumerate every aspect of agriculture in the United States. The quality of survey responses varies with survey and respondent. Ensuring that survey responses are valid, reliable, and internally consistent is vital to publishing accurate official statistics. NASS is undertaking modernization efforts to detect and edit survey responses through rule validation. These innovations include (1) a review and reconciliation of documented (e.g., written in business rules) and undocumented (e.g., only appearing in programming code) validation specifications, (2) distinguishing validation rules whose errors might be correctable with logical programming code or numeric methods, (3) using numeric methods, such as the Fellegi-Holt algorithm, and R software packages developed by Statistics Netherlands to automate response-level validation checks and error corrections, and (4) flagging instances of automated correction or validation errors for NASS analysts. This paper will describe the processes and procedures used for each step and highlight challenges and solutions to issues commonly encountered. 

Keywords: editing, validation rules, automated reconciliation

Thanks,

Albert Lee

Dear colleagues, here are two updates about the Statistical Computing in Action mini-symposium:

+ The deadline to submit an abstract for the lightning session is tomorrow (Monday, Oct. 2). Slots are limited. If you want to showcase your work related to statistical computing, please submit your abstract ASAP at asa-ssc.github.io/minisymp2023/abstract.

+ Group rate is now available (asa-ssc.github.io/minisymp2023/registration). Register once to host a "watch-party" for students and/or colleagues!

On Tue, Sep 12, 2023 at 6:13 AM Jun Yan <jyan.statistics@gmail.com> wrote:

The Section on Statistical Computing of the ASA is excited to host its online symposium (asa-ssc.github.io/minisymp2023) on Saturday, November 4, 2023.  The symposium, "Statistical Computing in Action", aims to demonstrate the remarkable potential and elegance of statistical computing and provide a platform to refine statistical computing expertise, enriching skill sets and problem-solving capabilities.  Additionally, the event endeavors to foster a collaborative and inclusive community that bridges the gap across various computing languages, encouraging knowledge exchange and mutual growth.

Registration and abstract submission are now open.  Please visit the website:  https://asa-ssc.github.io/minisymp2023

The program includes:

+ Keynote address by Simon Urbanek (Executive Editor of R Journal and Senior Lecturer of Data Science at University of Auckland).
+ Data Jamboree in which experts in Julia, Python, and R attack a data analysis in their respective languages.
    - Julia: HaiYing Wang (University of Connecticut)
    - Python: Shannon Taas, (Brigham Young University)
    - R: Lucy D'Agostino McGowan (Wake Forest University)
+ Lightning session with contributed talks from the community... That's you!
+ Panel discussion on open-source software, open data, and open computing featuring
    - Tracy Teal (Open Source Program Director at Posit)
    - Carol Willing (Python and Jupyter Core Developer, VP of Engineering at Noteable)
    - Achim Zeileis (Editor-in-Chief of Journal of Statistical Software, Professor at Universität Innsbruck)

The event is very cheap (as cheap as "free" for all student members of the Statistical Computing Section). We kindly request you to spread the word and share this opportunity with anyone who may have an interest in statistical computing and data science.

Please contact the committee with any questions.

Sincerely,

David Dahl (co-chair), Brigham Young University
Kun Chen (co-chair), University of Connecticut
Mingzhao Hu, Mayo Clinic
Jun Yan, University of Connecticut