Statistical Interpretation On Data And Its Implications

Abstract

Statistics in research serve as a tool for deceitful research, evaluating its data and portraying results drawn from it. Most research investigations produce a large amount of raw data, which must be adequately concentrated in order to be conveniently analyzed and used for more study. Even though a researcher does not always have the opportunity to employ statistical procedures in all of their details and implications, the science of statistics cannot be disregarded. However, classification and tabulation only partially succeed in achieving this goal; we must go one step further and create specific indices or measures to sum up the data that has been gathered and categorised. The process of generalization from small groups (i.e., samples) to the populous cannot be assumed until after this. In reality, descriptive statistics and inferential statistics are the two main subfields of statistics. Inferential statistics focus on the process of generalization, whereas descriptive statistics are based on the construction of specific indices from the fundamental initial raw data.