- Experiments can absolutely detect differences that matter!!! Experiments are designed to test a hypothesis, which is a question asked by the people who conducted the experiment themselves. When looking at the literature, these questions are usually very important, scientific questions that often benefit a large group of people, and in turn also challenge the current status quo which can, if found to be true, make a difference that matters.
- Causation means if something comes from the direct action of something happening. Correlation on the other hand is a pattern that occurs between things. So, if a study shows causation, that means that when the independent variable was manipulated in a certain way, the dependent variable Is the outcome of that direct manipulation. This result from the dependent variable is absolute. Whereas correlation will suggest a strong relationship between the independent and dependent variable, but won’t be as strong as an absolute answer, like causation. Causation does not mean correlation.
- The mechanism is how something works, detail by detail. A really good example of this would be how the mechanism of glycolysis works. This is an incredibly detailed mechanism with more than 10 steps to it, but at the same time this allows the reader to direct the process piece by piece. When looking at the literature, a good mechanism should have every single detail listed out, what those details do, and how they can affect other details of the mechanism itself.
- This is a hard question, and when looking at the literature it all depends on what the focus and hypothesis of the experiment is. Experiments, in my opinion, are half and half reality. An experiment’s purpose is to seek out the possible errors and outcomes of a suggest course of action. Reality is what happens in the moment, and likewise, an experiment is what happens in the moment. But with experiments, we can learn from our mistakes. In reality, we have to accept the consequences of them at the moment they happen. We can’t correct for them like we do in an experiment.
- When looking at the literature, confounding variables are what comes to my mind here. A confounding variable is something that scientists can’t really control for, and to be honest it does get a bit annoying because as humans we like to control our reality as much as possible. Nevertheless, we have to except these. Other reasons might be possible contaminations or errors in the scientist’s technique.
I personally believe that out of all of these, the question that matters the most when discussing controversy is #5. Out of my personal time reading scientific papers, it seems to be that people (scientists) always argue over what influences the result of an experiment. Even though humans can’t possibly know everything, this question will minimize discourse among scientists and therefore solve most of the controversy around scientific papers, of course in my opinion.
