Don’t Believe Everything You Hear

As a real [unbiased] scientist, we use the scientific method to test hypotheses. We all have biases. Its difficult to avoid that. When we say we have an open mind, do you really think that is true? Its absolutely not true. We are all leaning one way or another in our thoughts, feelings, and beliefs.

So how can we self-check ourselves on our thoughts? The Scientific Method.

We can use this in all walks of life. We can use it in law, politics, and social sciences. Its not just for biologists, geneticists, engineers, physical scientists, and the like. Here is what you do (this is the Andy version).

1. Observe something – Whatever the phenomenon is, observe something happening. But keep an open mind about it. Actually sit and observe. The more time you spend observing the better. Watch from different angles, different times of the day, and close and far. Don’t allow too many thoughts creep into your mind. Just let it happen.

2. Ask questions – brainstorm all the questions you can think of. Let the thoughts flow freely. Ask with an open mind from many different viewpoints. If you feel strongly about something from your background, ask questions your detractors might ask as well. Ask from the point of a child. Ask from your grandparents. Ask from all ethnicities of people. Ask from an animal point of view.

3. Develop hypotheses – in your mind and with your biases, make a statement of what you think the problem is even before any testing. This is your primary hypothesis. Now, propose the complete opposite question. Let’s say something is caused by "rain", the your null hypothesis is "not rain". Then, if, from the questions you pondered in #2, came up with other possibilities, propose a few alternate hypotheses as well.

4. Test the hypothesis – in an ideal world, you would devise a replicated, randomized, repeatable experimental design to test your hypotheses. It would completely take out bias in observations. And it would be statistically significant with reduced standard error and significance to the reliability of the science (say 95% probability with less than 20% standard error).

5. State the conclusions – if the data isn’t significantly relevant, then don’t dissuade your facts with lies. This is done so often. It is super easy to make statistics very relevant and factual. But its just as easy to hide the facts. When I was studying quantitative genetics, I asked our authority on the subject who was well-published in the area. I asked, what is the best test to use for this study? He said, whichever one gives you the best results. Huh? That’s when I realized what a sham most of our science is. This is why you publish in peer reviewed journals with reviewers who truly take an unbiased, critical eye at your work. Good ole boys let things slide. And I’m sure it happens a lot. State your conclusions with the least amount of bias as possible. Be totally objective. Maybe you lose your million dollar grant in the process, but that’s the price for good science.

In politics, we assume guilt. Innocence means nothing. If we don’t like someone, then they are guilty. You believe any Tom or Mary who comes along before you believe the person you don’t like. That is not right. Its not scientific. And its totally biased.

When we talk climate change, what is the null hypothesis? The fact is, climate does change. It has since the beginning of time. But when you ask cause and effect, make sure you point in the right direction. Its funny that someone will point out, we are having record breaking temperatures so it must be from man-made global warming. This assumes that the Industrial Revolution of the early 1900’s slowly caused a catastrophic rise in temperature. But then you see that the previous record was 1912 or maybe evidence scientifically validated as before the 1900’s. This was before the Industrial Revolution. So if its a record temperature, how was the previous record set? We have so much information that sea levels reached the highest mountains at some point. That dinosaurs or other extinctions occurred from a vast warming period. And this was all before the Industrial Revolution. Cause and effect. What really caused the problem?

Take out the bias. Especially if you are a scientist. Yes, you know better than to make suppositions not based on fact. Never believe what you learn from the News or in a College classroom. Believe me, bias prevails. Instead, think for yourself. Remove your own reasons why you discriminate against those who are different from you. If you believe in truth, then find the truth. Science isn’t emotion based. Its fact based. So don’t let your emotions get the best of you. Don’t justify your cause with lies.

Side note: When I was working on my Ph.D., we always had multiple side projects. My lab was a working lab. Everyone helped with each other’s projects. And our advisor had a lot of pokers in the fire. I was given an opportunity to write up a research article on a project that most of my lab mates worked on. I said "sure". When I started to do the statistics, nothing added up. I told my adviser there was nothing significant to report. There was way too much error. He said "OK", then gave it to someone who was working on their Master’s degree without a lot of statistics background. Well, she published the article based on flawed outcomes and I refused to take any authorship on the paper even though I did a lot of work on it. It came down to ethics and professionalism. We are all faced with pressures all around to produce results that support a cause. Its up to our own truth that allows us to live with ourselves. That’s what matters in the end.

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