When we look at the context of these benchmarks, they are very useful for comparing data on short notice to really put into perspective what we are looking at. It sets the standard to what is presented and lets the viewers based data off of the benchmark itself. The New York Times shows the New Hampshire Primary election results and how it has changed over time. The benchmark shows the race call standard and how it would measure up to the overall chances. It shows through the times of the night up to then next day on how the reports were growing and what was going on at the time.
This shows how Donald Trump won the votes of the people of New Hampshire in 2024. This visualization is showing in specific the expected turn out and the chances he had at winning in this specific visualization. In the image above we see both visualizations have what the race call was predicted to be and then we have what the chances were. In the artical linked here: https://www.nytimes.com/interactive/2024/01/23/us/elections/results-new-hampshire-republican-primary.html?smid=tw-nytimes&smtyp=cur
The New York Times spoke about how their data matched up with the one that concluded after the election. It's interesting that they compared the data to the live updates that were going on at the time. What impressed me was the dedication involved that it took to make sure all the information was up up to date. (Updates Above)
Lastly, what I want to talk about is the image of how the elections actually went. It's great that they posted how their estimates matched up in the state of New Hampshire. They gave live updates and what to expect during the actual process of the elections to keep viewers up to date on how the election for that state went.
You did a really good job at presenting this in a way I could understand it! I feel like going through this in the book I was wondering how all the information could be presented in a way that people could really understand but now that I'm seeing it like this it makes it a tad bit easier. In my opinion, I feel like we've done easier(less tedious) graphs. Well done!
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