![]() ![]() I’m not saying that Smith should’ve discussed all that-there’s a limit to how much can fit in one book- I’m just bringing it up to emphasize that distrust in science is not just an unfortunate byproduct of frauds like the disgraced primatologist and confused people like the ESP guy, it’s also something that a lot of people are fostering on purpose. And then there are the HIV/AIDS denialists, which seems more like contrarianism, and the covid denialists, which has a political angle. Familiar examples are industry-funded junk science on cigarettes and climate change, which then gets picked up by ideologues. One thing he doesn’t really get into is the political angle, the idea that bad actors are sowing distrust as a tactic to reduce respect for serious science. He also talks about misplaced technology enthusiasm, from bitcoin-as-savior to chatbots-as-AI. Smith has a broader perspective than just talking about junk science. Ironically, I think this sort of attitude is also behind some of the anti-reform movement by leading academics: they think science is just wonderful and they’d prefer if people just kept quiet about scientific errors or chalked things up to “the self-correcting nature of science.” Smith and I are more in the clear-the-rotten-apples-out-of-the-barrel camp. Rather, I want to talk about the big picture that Smith paints, which is the idea that science is very important to our lives, and bad science degrades that trust. Gary Smith is coming out with a new book, “Distrust: Big Data, Data Torturing, and the Assault on Science.” He has a lot of examples of overblown claims in science-some of these have appeared on this blog, and Smith takes pretty much the same position that I take on these things, so I won’t talk about that part further. ![]() Also, hey, let’s see the time series of divorces too! Posted in Statistical graphics, Teaching | 4 Replies Tigers need your help. Since they’re doing it as a bar graph anyway, I guess they could have the y-axis go all the way down to zero. Juliet, Tenn.Ĭool! I really like the idea of teaching statistical ideas using recent news.Īnd it seems they do this every week or two. and “Generation Battle: Is the World Getting Better or Worse?” by Taim of Gladeville Middle School in Mt. Here are some of the student headlines that capture the stories of these charts: “The Opposing Futures in the Eyes of Different Generations” by Helena of Pewaukee High School and “The Ages of Optimism” by Zoe, both from Wisconsin “Is Each Generation Making the World Better?” by Maggie of Academy of Saint Elizabeth in Morristown, N.J. The survey’s objective was to find out how childhood is changing in the 21st century, and where divisions are emerging between generations.Īre the 15- to 24 year olds (youth) more optimistic than 40+ year olds (parents)? Does the difference in optimism vary between the least wealthy and most wealthy countries? How might the degree of political stability, economic opportunity, climate change and the Covid pandemic affect the youths’ and parents’ responses? Which countries’ statistics surprise you? What do you think about the statistics for the United States? The survey sample was nationally representative and was conducted by landline and mobile telephone from February to June 2021. A report entitled “ The Changing Childhood Project: A Multigenerational, International Survey of 21st Century Childhood” offers all of the survey’s findings with its 32-question survey and its methodology by country. 17, 2021 New York Times Upshot article “ Where Are Young People Most Optimistic? In Poorer Nations.” It displays statistics from an international survey of more than 21,000 people from 21 countries conducted by Gallup for UNICEF. The questions are intended to build on one another, so try to answer them in order. What’s going on in this graph? Create a catchy headline that captures the graph’s main idea. How does this relate to you and your community? They start with the above scatterplot and then ask a series of questions: ![]() Paul Alper sent us this fun feature from the New York Times that teaches students how to read a graph. ![]()
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