Data can be misguiding if the sampling is not done properly. A random selection without background knowledge or without specified criteria leads to misinterpretation of the data. Another cause of misinterpretation is difference in causation and association. Variables after another but one variable does not cause another. One of the manipulated areas in medical world is pharmacy. Pharmaceutical companies use misguided data in competitive markets. Generic medicines for same purposes are branded out and to advertise it misguiding database is used. The most important thing to be considered while interpreting or predicting an outcome of a statistical analysis is a well balanced and well selected population. Sample is to be selected considering different aspects of the problem so that the result will not be biased. This demands the proper understanding of the statistical tools and how to select the sample population. Moreover, the sample size should be sufficiently large enough to get into more finite conclusions.
Ercan, I. (2007). Misusage of statistics http://www.bioline.org.br/pdf?gm07030
in
medical
research.
Retrieved
from