Covid cases vs. Covid shots per person, where each dot is a state. By pure coincidence, states with fewer vaccinations per person tend to have more cases.pic.twitter.com/IGg97JVeoF
I'm worried that the baby thinks people can't change.
You can add location information to your Tweets, such as your city or precise location, from the web and via third-party applications. You always have the option to delete your Tweet location history. Learn more
Add this Tweet to your website by copying the code below. Learn more
Add this video to your website by copying the code below. Learn more
By embedding Twitter content in your website or app, you are agreeing to the Twitter Developer Agreement and Developer Policy.
| Country | Code | For customers of |
|---|---|---|
| United States | 40404 | (any) |
| Canada | 21212 | (any) |
| United Kingdom | 86444 | Vodafone, Orange, 3, O2 |
| Brazil | 40404 | Nextel, TIM |
| Haiti | 40404 | Digicel, Voila |
| Ireland | 51210 | Vodafone, O2 |
| India | 53000 | Bharti Airtel, Videocon, Reliance |
| Indonesia | 89887 | AXIS, 3, Telkomsel, Indosat, XL Axiata |
| Italy | 4880804 | Wind |
| 3424486444 | Vodafone | |
| » See SMS short codes for other countries | ||
This timeline is where you’ll spend most of your time, getting instant updates about what matters to you.
Hover over the profile pic and click the Following button to unfollow any account.
When you see a Tweet you love, tap the heart — it lets the person who wrote it know you shared the love.
The fastest way to share someone else’s Tweet with your followers is with a Retweet. Tap the icon to send it instantly.
Add your thoughts about any Tweet with a Reply. Find a topic you’re passionate about, and jump right in.
Get instant insight into what people are talking about now.
Follow more accounts to get instant updates about topics you care about.
See the latest conversations about any topic instantly.
Catch up instantly on the best stories happening as they unfold.
Covid cases vs. Covid shots per person, where each dot is a state. By pure coincidence, states with fewer vaccinations per person tend to have more cases.pic.twitter.com/IGg97JVeoF
Covid cases vs. Covid shots per person By pure coincidence, states with fewer vaccinations per person tend to have more cases.pic.twitter.com/kBNzBwqMSm
I don't know if this is useful input of not, but one of the reasons programmers such as myself don't take a lot of economic analysis seriously is because we work with large volumes of complex data daily, and we would never take a chart like this as indicating something.
What that resembles to me is a chart where you have isolated a relatively unimportant variable. If I had that outcome on a dataset, I would assume that I needed to change my analysis to find out what was really going on.
Out of curiosity, if shots per person is a relatively unimportant variable, what is an important variable in this context?
I have no idea, I don't study this problem. But looking at a chart with ~50 data points with that kind of spread and a very low-slope trend, I would just assume that whatever I graphed was merely a weak correlate to whatever the real important variables were.
Since there are so many variables here (density, level of interaction, mask compliance, "superspreaders", transit type, etc.), and many of them could correlate with whether or not people are interested in getting vaccinated, I would dig much deeper before concluding anything.
Point taken. I think an appropriate thing to say is that this is suggestive evidence that vaccines work, though this graph in and of itself does not establish the causal link.
I mean, I suppose, but if you wanted to demonstrate that with a graph, would the graph be number of cases in vaccinated people vs. number of cases in unvaccinated people? If the goal is to demonstrate that vaccines work, there are much better graphs than this one.
Ultimately, the best graph to show they work is a graph from a randomized control trial.
And we already know that data very well, since the Phase 3 results of the mRNA vaccines were conclusive and were not low-sample-count, high-noise datasets like the one in this graph.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.