Science is falsifiable. Or at least, this is what I (like many Americans) learned in many of my high school and college science classes. Clearly, the idea has appeal among scientists and non-scientists alike. But what exactly does “falsifiable” mean? And why is it valued by some scientists, but dismissed or even considered actively harmful by others?
Entries by Evan Arnet
Against “the study”
Science journalists are always announcing the results of the latest study. The more bizarre and controversial, the better. A recent study is, almost by definition, cutting-edge research — what better way to tap into the pulse of science? Except, the latest and greatest research is just as often wrong. The concern is not simply with hype. Rather, the problem is the “study.” As a unit of scientific research, it leaves much to be desired, and for those who are unfamiliar with the practices of the scientific community, how to interpret a lone study can be deeply confusing.
A 70% chance to win? The tricky math of election forecasting
The election is almost here and the election forecasters are in full swing. As of October 23rd, the Economist gives Biden a 92% chance of winning, and FiveThirtyEight has him winning 88 out of 100 “simulated” elections. How should we interpret these claims? If you have a coin and you flip it a thousand times, and it lands on heads 500 times and tails 500 times then you may infer it has a 50% probability of landing on heads and a 50% probability tails. Sounds simple, except, we’re not going to run this election thousands of times, we’re only going to run it once.
How many people has COVID-19 really killed in the U.S.?
In late August, the Centers for Disease Control and Prevention (CDC) updated their provisional death counts page to indicate that COVID-19 was the sole cause of death listed on death certificates in only 6% of cases. This fact was interpreted by some as only 6% of reported fatalities, or around 10,000 people, actually died of… Read more »
COVID-19 at IU and the importance of waiting for the evidence
Before classes had even started this semester, pictures of student parties began to circulate on social media. A college experience had been promised, but not everyone read the fine print about the degree of isolation and social distancing that would be required. The reactions ranged from indifference, to abject horror, to finger wagging, to smug… Read more »
Greedy scientists and their grants
In 2009, there was a faux controversy called Climategate, in which a climate change research server was hacked and private emails were leaked. This event was then spun to create the impression that human-caused climate change was all a big conspiracy. What exactly was the alleged motive for these scientists to make up climate change?… Read more »
Science, Eugenics, and Twitter
On Saturday, February 16th, biologist and noted public intellectual Richard Dawkins tweeted about eugenics. Dawkins provided no context. No ongoing dispute he was inserting himself into. No obvious interlocutor. And certainly not anything as convenient as a few previous tweets to set the stage for this surprising announcement. As someone interested in science communication, genetics, and ethics, I find it worth exploring how he screwed up, how he didn’t screw up, and what any of this means for science…
Strength in Numbers? The Meaning of Scientific Consensus
“Science, on the contrary, requires only one investigator who happens to be right, which means that he or she has results that are verifiable by reference to the real world. In science consensus is irrelevant. What is relevant is reproducible results. The greatest scientists in history are great precisely because they broke with the consensus.”… Read more »
Dispatches from the statistics wars
We recently took a guided tour of statistical significance, in which we focused on how the media often fails to correctly interpret statistical information. But, journalists are not the only group that is tripped up by statistics. The scientific community itself has been engaged in deep debate about the proper use of statistical methodology. These debates… Read more »
The perils of publish or perish
Academia is a tough career choice. The pay is low (especially for graduate students), the hours are long, and the job market is uncertain. Those entering the field often receive this simple advice — “publish or perish.” Publications are the central method by which people are evaluated in academia. One either continually publishes papers, ideally… Read more »