DNP 801 Topic 6 DQ2
What are misrepresentations that can occur while reading other’s work and using its data? How can do you determine when data is a useful source of evidence for a project? Is it possible to misrepresent data and conclusions using statistics? Why or why not? How? Researchers may leave out data that are not in support of their research hypothesis. Data can be concocted if the data was lost or process of data collection was interrupted. If this occurs, the conclusion from the research could be altered. The main scope of the data or assessment findings can remain hidden from readers who are unable to assess the validity of the results accurately. This can lead to misrepresentation. To determine when a data is a useful source of evidence for a project, the data has to be free of misleading and biased evidence. Validity and Reliability are the primary determinants when checking if a data is free from misleading and biased evidence. According to Topkaya, Sahin, & Meydan (2017), data reliability is defined as the length to which an assessment or data is consistent while data validity refers to the integrity of the method used in carrying out the research.
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