Why is it important to consider experimental error in all the empirical results presented?

Empirical studies are results of analysis of data based on actual observation or experiences in the field. When conducting an empirical study, quantitative and qualitative approaches are employed, including:

1.      Providing  data

2.      Emphasizes features of a new condition

3.      Describes the current status of existing condition

4.      Highlight associations between variables, but cannot establish causality, and

5.      Suggest hypotheses which can be tested in analytical studies

Qualitative empirical studies provide deep contextual data to help us understand a situation, but it cannot be used to establish its prevalence or incidence.  It cannot be generalized also to highlight the statistical relationship between variables. If the aim is to measure the relationship, the quantitative methods should be used. A cross-sectional survey with large sample size is needed to describe the who, what, and where of a situation. Still, it cannot answer the why question.  In order to answer the question of "why",  an analytical or experimental study is needed. Experimental error is an important consideration here considering lapses or inaccuracies in the qualitative and quantitative data. 

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