The Harvard Data Science Review (HDSR) podcast aims to show news, policy, and business through the lens of data science. Each episode is a ‘case study’ into how data is used to lead, mislead, manipulate, and inform the important decisions facing us today
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The Harvard Data Science Review (HDSR) podcast aims to show news, policy, and business through the lens of data science. Each episode is a ‘case study’ into how data is used to lead, mislead, manipulate, and inform the important decisions facing us today
Polling for 2024 U.S. Election: What Should Voters Look for and Trust?
Harvard Data Science Review Podcast
29 minutes 55 seconds
1 year ago
Polling for 2024 U.S. Election: What Should Voters Look for and Trust?
As the U.S. approaches another presidential election, many of us are contemplating our beliefs, staying informed about election news, and at times, questioning the integrity of the voting polls. This month we delve into the upcoming House, Senate, and presidential elections with the help of two political polling experts. Where can we find reliable polls amidst an ocean of information? Has the rise of AI and other technologies affected the 2024 election? How are election outcomes determined? Which voter demographics might lead to surprising election results? Join us for an insightful discussion on these topics and more on the Harvard Data Science Review Podcast.
Our guests:
Kai Chen Yeo, pollster and partner at Echelon Insights, a next-generation opinion research, analytics, and intelligence firm.
Scott Tranter, Head of Data Science at Decision Desk HQ
Harvard Data Science Review Podcast
The Harvard Data Science Review (HDSR) podcast aims to show news, policy, and business through the lens of data science. Each episode is a ‘case study’ into how data is used to lead, mislead, manipulate, and inform the important decisions facing us today
