The headlines catch the eye: [link url=”http://www.cnn.com/2015/12/28/us/severe-weather-us/index.html” title= “Dozens Killed in Massive Storms”] says CNN. The question then arises: ‘Is there knowledge out there that could aid with preparation, but which we’re not using?’ The answer, of course, is: ‘Probably so.’ One question would be whether or not the tornadoes that swept through Dallas in the past few days could have been expected, or whether they are in fact a statistical anomaly.
NOAA’s National Weather Service Storm Prediction Center keeps some [link url= “http://www.spc.noaa.gov/climo/torn/fatalmap.php?yr=2015” title= “awesome data.”] With a little digging it was possible to determine the number of tornado deaths for each given month over a span of years. Like a good researcher (which I can only imitate) I formed a theory and a hypothesis:
Theory: Tornadoes cluster two time per year, in the spring and late fall.
Hypothesis: Examining the data from 2004 – 2014 will provide evidence that confirms the theory.
Data:
January – 17
February – 122
March – 86
April – 484
May – 298
June – 29
July – 7
August – 12
September – 13
October – 10
November – 57
December – 19
Conclusion: The hypothesis is disproven and the theory is unsupported.
So, in everyday language: Research can be a painful experience for the researcher. I was firmly convinced going in that my theory was correct, and my hypothesis would be proven: instead, the data tossed them to the ground and walked all over them. Although being somewhat hard on the ego, that’s ok, because the analysis prevented me from making several bad recommendations that may have resulted in wasted resources and ineffective operations. That’s why we do research at all–to prevent these kinds of errors.
Although this example didn’t turn out anything like I expected, it’s still possible to derive several valuable conclusions from the effort:
- Tornadoes concentrate in the spring. That’s when preparation must be at the highest, resources in place, public aware, finger on the trigger, all systems go, etc.
- Preconceived notions are a dangerous thing. Before the research, I ‘knew’ that there would be a cluster of tornadoes in the fall. That was wrong. How many other things that I ‘know’ are also wrong? How many things that you ‘know’ are wrong?
- Data denial is a dangerous thing. For how many more inches of sea level rise, droughts with accompanying refugee crises, resource wars, etc., will we go through before we accept the data driven, scientifically proven fact of human-caused climate change? How many people will we disservice and endanger before we do?
- Research is valuable! It’s not necessary to be fancy about it–my little exercise here, which took maybe half an hour, provided valuable information that could prevent mistakes. So before you make that mistake–go do your research! Find the factual data! Believe the data! Then repair your ego if necessary, but only AFTER you’ve done your service to the public.
Happy researching and a joyous and effective New Year!
Comments are closed.