As a current data analyst, and a data analyst as a major role in most of the professional positions I have held in the past 13 years; I am quite accustomed to people questioning data.
Most of the time compiled data is unquestionably passed along and used for managerial decision making. Sometimes after someone looks at it, new parameters need to be put in because either more information is needed or there was a miscommunication about what was wanted. And on occasion I may have made an error in inputs or pivoted an incorrect field. It happens. To avoid a circumstance of error, my co-workers and I usually do a second review of one another’s work to ensure that we pulled and compiled an analysis correctly.
Once it’s sent out, we often answer questions about parameters, assumptions, categories, etc. No one has ever accused us of being biased. If something seems wrong or the requestor doesn’t like what the data shows, there are other people who can run the same thing. When the same results are shown over and over by different groups whether or not it’s within my local organization or around the country – it ends up being facts that don’t have a “belief” on whether or not one agrees with them.
On some rare occasion a manager or physician will find one or two lone people who will run data to support what they need. Or they unknowingly asked someone who doesn’t do it often enough to know what to put in, and they just happen to get results that support a new position, that supports a clinic is more full than it really is, or some other result the individual wishes to be true.
However, there are measures in place to ensure that when other results overwhelmingly outweigh a small number of results; what the vast majority has found is what is used. This is also true in clinical research which I’m also very familiar for obtaining data for as a side job.
Peer review is a common practice in professional papers, journals, and research. In my first job at the VA before any data analysis, the physician I worked for was a peer reviewer for several medical journals in her field around the world. The process is blind – meaning, you have no idea who wrote the paper or pulled the data in the paper. And the writer has no idea who reviewed it. The reviewer makes suggestions to the editor and writer about whether or not the paper has validity, if more information is needed, etc. It’s a brilliant process that has worked for decades and lead to serious advances in all areas of life.
That is what I have found disturbing about COVID. COVID isn’t the first thing that is indisputable but ends up becoming a “belief”. But it does seem now like things questioned in the past are now forums for long angry discussions, some become political points, and others are ripping apart family and friends. I really don’t understand this.
The facts and data shows-
- COVID isn’t made up
- COVID numbers aren’t made up
- Climate Change is a real thing
- Racism is real
- Sexism is real
At some point – where the bell curve flattens (around 98% or so; or arguably even before) it’s time to believe the majority. When something is new – such as the world is flat, I really understand that it can be hard to believe. But when 98% of the studies show the world is indeed round, it’s kind of time to flip the flat earth viewpoint.
No actual data or studies show most of the poo that is tossed around about political candidates or parties. Some clown (or brilliant jokester) either in the US or a foreign country is probably laughing in their garage about Americans eating up whatever nonsense they drummed up hook, line and sinker. These are rinky dink memes and articles and unvalidated data. Even articles and opinion columns in well respected news media are not backed by any studies or data. We would hope they stay neutral (but they clearly don’t); so our only real hope for good information is from the professionals who do this for a living.
You can have an opinion, but when it conflicts with overwhelming data – I have to side with the person who posted this on social media.
Beliefs are not facts. And that is a fact.
Namaste
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