Trust the Scientific Method

I believe that scientific method gives us the best chance of finding the truth through one variant of experiment or another.  That doesn’t mean that research flaws can’t slip in and give us incorrect conclusions that can be accepted for a while.

I’ve just noticed some articles about African Neanderthals – these guys may have ranged from the Med to Jo’berg.  It conflicts with all my training – that sub-Saharan Africans lack Neanderthal genetics has been an article of rather amusing faith. 

I researched the correlation between technology – cell phones, mostly – and Hutterite outmigration.  The data looked fine – the statistical probability of my research not being significant was extremely low – yet one interview with an old Hutterite minister, and an article in the Mennonite Quarterly Review brought forward a confounding situation.  The presence of a group called the Arnoldleut, and their earlier incorporation and eventual ejection from the colonies was far more significant than the technological changes I studied.  While that discovery was part of my research, it was also luck – a secretary with whom I had worked arranged the interview not so much to help my research but to create a situation where a runaway could spend an evening back on the colony visiting with her mother as I interviewed the minister.  I trust the scientific method – but without that last interview, I would have published nonsense . . . and my last interview occurred because of a secretary’s kindness in finding a way for a grandmother to meet her new grandchild. 

I believe that scientific method is the best way we have to get facts – but all of our results are subject to further examination.  The physical laws that Isaac Newton developed were all the results of observations that occurred within earth’s gravity and atmosphere – yet most of the universe is vacuum and free fall.  The ability to observe the very small increased after Newton – and we’ve moved into a time when Quantum became the word to describe a form of physics that was not available for Newton to observe. 

I trust scientific method.  Scientific method insists that all of our findings are tentative . . . I am unlikely to be the last person to research Hutterite outmigration.  My findings are correct (due to a secretary getting me one more interview) and I was saved the embarrassment of publishing an incorrect explanation of that outmigration.  Newton’s laws are in print, and useful – but later researchers till the fields of quantum physics.  The results of scientific inquiry are always tentative, they can always be questioned.  It’s worth remembering that Piltdown man spent nearly 40 years in mankind’s family tree before the hoax was conclusively proven in 1953. 

Science does not move through consensus nor certainty.  Trust the method – but question the results.  We do not prove with statistics – statistical methodology just quantifies the likelihood of something occurring due to random happenstance.  We take that statistical data, and infer causality.  I’m one of the lucky ones – Mary Kidwiler arranged an opportunity that kept me from the embarrassment and mockery that accompanies publishing a scientific blunder.  Follow the scientific method – but remember, all conclusions are tentative and subject to revision.

Community, Demography

Covid’s Mask and Pascal’s Wager

According to the Internet Encyclopedia of Philosophy, “Blaise Pascal (1623-1662) offers a pragmatic reason for believing in God: even under the assumption that God’s existence is unlikely, the potential benefits of believing are so vast as to make betting on theism rational.” As a stats guy, I could write this from memory, as a scientist, I need to cite a source.

Pascal’s statistical argument is a gambler’s view of the universe – the cost of believing, of the ante, is so small compared to the infinite reward (the size of the pot).  I worked with an accountant who had a system for buying lottery tickets – his break from understanding Pascal was that both cost and reward in the statistics of lottery cards are finite – the odds really can be calculated.  Lotteries are a tax on people who don’t want to do the math.

Covid is also a game for statisticians.  It’s still at a point where we have a bunch of unknowns, but there are fewer unknowns than there were 6 months ago.  Then the Diamond Princess was a horrifying news story – now it is data, as taken from “A total of 712 people were infected with COVID-19 on the Diamond Princess cruise ship – 567 passengers and 145 crew members. The cruise ship, which had more than 3,500 people on board, was quarantined for around two weeks. All passengers and crew members had finally disembarked the ship by March 1, 2020.”

Wikipedia shows 14 deaths among the 712 infected people on the Diamond Princess.  Somewhere right around 2%.  About the same as Texas and California, and lower than New York, New Jersey, and Massachusetts.

We’re still looking at less than perfect representative numbers – but Diamond Princess has provided some data:  roughly 20% of those exposed between January 20 and February 19 wound up infected.  In March, we had estimated R0 values from 1.5 to 3.5.  Now, we have Rt values (Average number of people who become infected by an infectious person with COVID-19 in the U.S. as of October 17, 2020).  Those numbers vary from 0.91 in Mississippi to 1.31 in New Mexico.  Montana scored 1.2. 

Generally speaking, in the absence of data, we have a tendency to assume the worst.  We have data now.  The actual infectivity is lower than the initial data – perhaps because the precautions have been effective, perhaps it is related to the fact that 80% of the people on Diamond Princess did not catch covid.  Correlation is not causation.  Causation is inferred from statistics, not proven.

This week, an article from the American Society of Hematology stated: “Blood type O may offer some protection against COVID-19 infection, according to a retrospective study. Researchers compared Danish health registry data from more than 473,000 individuals tested for COVID-19 to data from a control group of more than 2.2 million people from the general population. Among the COVID-19 positive, they found fewer people with blood type O and more people with A, B, and AB types.

Making statistics personal is a challenge – data suggests that my risk factors are increased by age (70), height (6’3”), asthma, and diabetes.  How much we don’t know – for neither my asthma nor the diabetes scores particularly high.  My risk factors are reduced by my blood type.  So let’s look at masking.

My mask is like Pascal’s wager – it seems logical that any level of masking will reduce transmission.  The question is: “How much?”  I don’t have that answer.  Does my mask protect me significantly?  When I have been in surgery, the surgeons and medical staff were masked to protect me.  Similarly, is my mask to protect others?   Business Insider offers an article comparing mask effectiveness, but cautions that “Mask studies should be taken with a grain of salt.”  My mask is like Pascal’s wager – and I hope wearing it adds a sense of security. It costs me little to wear it.