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why is planning experiments important to scientific study

This adds to the credibility of the original findings. People do make inadvertent errors, and sometimes unexpected variables are left uncontrolled. There are ra
re but important examples of researchers just out-and-out faking data, sometimes because they are simply dishonest, and sometimes because they are so totally convinced that they are right (only to be exposed and humiliated, usually ending careers).   There is also the nature of information itself, and its analysis from a statistical point of view.


Sometimes, for no reason other than "the fall of the dice", a result may survive a statistical analysis as significant, when it is not. [a false positive] This has nothing whatever to do with dishonesty or bad research technique. When statistical models are used to analyze data, the concept usually is to compare the real experimental data against theoretical models that are built on all possible outcomes assuming that there is no experimental effect whatsoever.   A Little Added Detail: In other words, say that you get a certain result on a statistical analysis.


You go to your tables and you see that results just like yours do come up by chance alone, but only one time in a thousand. This "one time in a thousand" comes from the fact that the theoretical model for the test you are using represents thousands or tens of thousands (or more) of theoretical results based on completely random data. So when you see that your results are similar to the "one time in a thousand" frequency in the model, you have considerable confidence that your results represent a real effect, and not the rather unlikely "one in a thousand" outcome.


Confidence never actually reaches absolutely 100%, But we can (and should) set the desired confidence level even before we gather one bit of data, and can then carry on with our work. If man did not understand scientific principles then we would not have any of the technology that you enjoy today. In order for individuals such as Einstein, Da rwin, Brunel or Dyson to become interested in and take advantage of science, the general population must have exposure to scientific understanding.


Also, if we didn't know the causes of events then we might well pass the responsibility on to "God" or some other form of superstition and, for example, not know how to predict natural disasters. As an individual in the modern world, it depends really on what you do for a living. I am studying to become an engineer, so without understanding scientific principles, I would get nowhere at all.

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