TAMU PhD Statistics Graduand. Statistician at Ipsos Public Affairs. Fan of polls, politics, policy, and Bayesian statistics. My opinions are my own.
Aug 6, 2023 • 19 tweets • 3 min read
My next session is “Machine Learning and imputation techniques for survey design and missing data”. The first presentation is “A Machine Learning Approach for Imputation of Missing Race and Ethnicity Information in Health Survey” by Hui Xe from CDC. #JSM2023
Hui states that the purpose of this talk is to develop a machine learning approach to impute missing race/ethnicity data. Race and ethnicity data is often missing and can occur not at random. The distribution of race and ethnicity is often unbalanced. #JSM2023
May 10, 2023 • 31 tweets • 10 min read
My next session is “Like it or Not? Survey Recruitment and Data Collection using Social Media”. Presented by @trentbuskirk#AAPOR
Trent starts by saying this survey is a pilot study to conceptually cover individuals who have professional experience about privacy. Trent first starts with a literature review of using social media as a method of recruitment. #AAPOR
May 10, 2023 • 22 tweets • 8 min read
My next session at #AAPOR is “Things that Divide Us: Ideology, Identification, and Information”. The first talk is “Fake News Interventions: Effective for Both Strong and Weakly Identified Partisans?” presented by Joseph Sandor.
Joseph first explains that while people have a motivation to share accurate information on social media sometimes people share things that are inaccurate. Joseph is presenting the results of an experiment where users rated a headline’s accuracy before sharing. #AAPOR
May 10, 2023 • 38 tweets • 14 min read
I’m excited to be at #aapor this year. The first session I’m attending (and live tweeting) is “Assessing the Polls: Measuring Bias and Vote Choice”.
The first presentation is “It's Not Personal: Evaluating the Impact of Asking for Voters By Name” presented by Travis Brodbeck and Madeline Harland of @SienaResearch.
Nov 10, 2020 • 12 tweets • 3 min read
I’ve looked into statistics about voter fraud and I find it hard to believe there is the necessary level of voter fraud to flip this election. If Biden wins AZ and GA you have to overturn the results of 37 electors. The easiest way to do that is to contest GA, AZ, PA.
Biden is ahead by this many votes in these states:
GA: 12338
AZ: 14746
PA: 45103
Total: 72187
Now these aren’t official numbers but bare with me here. So we need about 72k fraudulent votes all for Biden to flip the election. That number needs to be put in perspective.
