Are you what some would call an inquisitive person? 
Have you ever tried to interpret some new research to work out what it means in the grand scheme of things? Understanding research can be challenging and there are some common mistakes that people make.
Here’s an historical tidbit that might interest you. Between 1860 and 1940, as the number of Methodist ministers living in New England increased, so too did the amount of Cuban rum imported into Boston, and they increased in an extremely similar way. Are we to assume that Methodist ministers purchased lots of rum? No, that would be silly. But in reaching that incorrect conclusion, we’ve made the far too common mistake of confusing correlation with causation.
Just because two quantities are correlated does not necessarily mean that one is directly causing the other to change. Correlation does not imply causation, just like cloudy weather does not imply rainfall, even though the reverse is true. To establish cause and effect, we need to go beyond the statistics and look for separate evidence of a scientific or historical nature and logical reasoning. Bad weather usually means that sales of umbrellas rise but buying umbrellas won’t make it rain. But, even where causation is present, we must be careful not to mix up the cause with the effect, or else we might conclude, for example, that an increased use of heaters causes colder weather.
Correlation is very often mistaken for causation in ways that are not immediately obvious in the real world. When reading and interpreting statistics, one must take great care to understand exactly what the data and its statistics are implying, and more importantly, what they are not implying. We must always insist on separate evidence to argue for cause and effect and that evidence will not come in the form of a single statistical number or study.
Unfortunately, analyzing statistics, probabilities and risks is not a skill set wired into our human intuition and thus it is all too easy to be led astray. When an abundance of data is present, bits and pieces can be cherry-picked to support any desired conclusion and it can be hard to spot without knowledge of the original, complete data set.
Significant doesn’t mean important. Some effects might be statistically significant, but so tiny as to be useless in practice. Take for instance a study of 22,000 people that found a significant association between aspirin and a reduction in heart attacks, although the size of the result was miniscule. The difference in the likelihood of heart attacks between those taking aspirin every day and those who didn’t was less than 1%, and when considering the possible costs associated with taking aspirin, it is dubious whether it is worth taking it at all. If a treatment promises to lower our risk of a condition by 50% but the risk of actually having or contracting that condition is less than .0002%, then the treatment is basically useless.
A common battle-line between global warming, climate change, climate disruption activists and people who actually know a snake oil salesman when they see one is all that faked scientific studies pushed by the United Nations and all those crazy outlandish scare tactics pushed by the left to relieve American taxpayers of their money. Don’t think scientists would fake a study? In 2014, a pair of economists, Fuhai Hong and Ziaojian Zhao admitted in a published peer-reviewed paper in the American Journal of Agricultural Economics, that lying and exaggerating the issue of global warming, climate change, climate disruption to advance an extremist environmental agenda was a good thing. They wrote: “It appears that news media and some pro-environmental organizations have the tendency to accentuate or even exaggerate the damage caused by climate change.
This article provides a rationale… We find that the information manipulation has an instrumental value, as it ex post induces more countries to participate in an IEA, which will eventually enhance global welfare. From the ex ante perspective, however, the impact that manipulating information has on the level of participation in an IEA and on welfare is ambiguous.” In other words lying and fraud are okay as long as they produce the desired results. Hmmmmm!
Use the brain God gave you. Look past the obvious and question the end results. That applies not only to science but politics.
“Science is the search for truth, nothing else; when scientific truth is trashed for personal gain, the world is in deep trouble!” Robert Ashworth
