Abstract:

As a result, it can be said: · If the difference did not come out when expected, you must first find out if your measurements were mistaken in the points discussed above. If you have the possibility, it is right that you fix and repeat these errors and errors. If you don’t have the possibility, which is not in most thesis studies, you should read this study about these shortcomings and errors you realize and warn those who will do other studies. But you should never apply for the verification path for compulsory testing by playing with data etc. because there is no difference! That’s what’s wrong! · If there are no faults and errors addressed above, don’t worry (except that the research phantom and the problem are incorrect), you may have produced information about what you think is true will not be true. It is also important that your tests are not verified. Showing that a information everyone knows correctly is wrong is even more important than confirming your expectations: “The hair is long, but the mind is long!”