Posted on 10/27/2013 6:28:44 AM PDT by Berlin_Freeper
A SIMPLE idea underpins science: “trust, but verify”. Results should always be subject to challenge from experiment. That simple but powerful idea has generated a vast body of knowledge. Since its birth in the 17th century, modern science has changed the world beyond recognition, and overwhelmingly for the better.
But success can breed complacency. Modern scientists are doing too much trusting and not enough verifying—to the detriment of the whole of science, and of humanity.
Too many of the findings that fill the academic ether are the result of shoddy experiments or poor analysis
(Excerpt) Read more at businessinsider.com ...
They are simply pimping for the next gov’t grant. Far too many “scientists” are just feeding at the trough.
In the area of Climate Change this is blatant, and obvious, and well known. In other areas, it is perhaps more subtle. But because the money is often good, the scientists will quite often tell people what they want to hear.
Correct! For any study or “research” you need to ask who paid for it. That will often explain the results.
Just follow the IPCC’s example: throw out the data which doesn’t match your predetermined conclusion, and keep whatever is left. Their conclusion: global warming is everywhere! Well, at least everywhere we decide to look.
Start with a hypothesis and diminish any data that does not support it.
Its like the old joke about accountants who are asked what 2 + 2 is. The answer: “what do you want it to be?”.
One of the few "Sciences" that has its theoretical underpinnings based on the discoveries and logic of Karl Marx.
Either Karl or Harpo.
The Modern Scientific Method:
1. Who’s paying the bills?
2. What answer do they want?
Let’s see: Politicians lie, business and finance people lie; religious leaders lie; economists lie; academics lie and now scientists lie. Interesting!
An under stressed issue is the way “journalists” report on science. Remember, you’re most often reading what some half-educated scribbler thought the scientist said and then pasted it with a misleading headline.
Ah—one of my pet peeves as a scientist is the use of a large epidemiological or observational study to “prove” the preconceived bias of those conducting the study.
I chose a field of study where we set up control groups that are exactly the same as the test groups, except for the item being tested. We then run the results through a statistical test for significance. We run the exact same experiment two more times (because, in this field, three is a magic number). If we see the same results from three identical experiments, we accept them as valid. I have, many times, rejected what looked like an interesting result because the observed result turned out to be within the normal variation of the system.
Most scientific fields, however, do not have the luxury of setting up absolutely identical control and test groups. That is a big part of the problem.
Another part of the problem is that many of those doing the studies are not actually trained in research methodology/philosophy. This happens a LOT in clinical research. A lot of data is collected, numbers are crunched, correlations are found, and the study leaders jump to the conclusion that finding the correlation means they actually proved something. No. To use a common and well-publicized example, drinking soda has NOT been shown to cause obesity. Sure, enough obese people drink soda that there is a real statistical correlation between soda consumption and obesity—but that does NOT establish a causative relationship. Yet we see study after study, breathlessly publicized by scientifically illiterate journalists, that “show” that soda causes obesity because they documented what we already know, that there is a correlation between level of soda consumption and obesity. Not one of those studies has taken the next step and examined why the correlation exists. Similar flaws may be found in many studies. Unless the work begun in the observational/correlational study is continued, and biochemical mechanisms for the effect are dissected and verified, the studies are meaningless.
Thanks Berlin_Freeper. Case in point, the Global Warming / AGW Hoax.
>laboratory-based science is of course the best; but, it can be very expensive and is often impossible
>example, identical twins separated at birth; could you think of a better way of controlling for genetic influences on human behavior? But, how many trials do we have?
>example, splitting countries into two halves, East and West Germany, or North and South Korea, and see how communist and democratic governments work out. Again, how many trials do we have?
>so, mostly, in medicine, psychology, the social sciences, education, business, we have no choice but to use statistics.
>having said these things, I agree with the argument presented, that much of what passes for statistical work is flawed.
No question; it even supports my contention. It wasn’t until people began looking behind what the “journalists” we’re writing that the ludicrous nature of the IPCC and others became apparent.
It is not that difficult to test: Skip soda for a few weeks and check the result, but that is not epidemiology.
No, it isn’t, especially if you set up a test and control group where the only difference between the groups is that one consumes soda and the other doesn’t.
I wish the problem of obesity really could be pinned on something simple like soda consumption. I don’t drink soda—I should be rail thin. But no, I have to watch my diet and exercise regularly, which are both considerably more difficult than simply avoiding soda.
Disclaimer: Opinions posted on Free Republic are those of the individual posters and do not necessarily represent the opinion of Free Republic or its management. All materials posted herein are protected by copyright law and the exemption for fair use of copyrighted works.