However, business professionals are not data scientists, and data scientists generally do not have the same level of subject matter expertise that some others in the organization possess. Dr. Daniele Fanelli, Research Fellow, The University of Edinburgh: In my research, there is pretty good evidence that the frequency of positive results, as opposed to results that do not support the hypothesis that was tested in the study, have been dramatically increasing over the last twenty years. Interpreting data helps comprehend text books, graphs and tables. There are three components required to make an expert business decision based on data : Statistical knowledge/ Quantitative aptitude Domain Knowledge Business Context To make data driven decisions using a mathematical approach, it is important to have a perfect blend of all the above factors. Consequently, data literacy should be considered a life skill. Although there are roles in between, such as business analysts, an imbalance of data expertise and domain expertise can result in the misinterpretation of data. Data &Society Research Institute datasociety.net Organizations may also face challenges in making sense of the data they have access to--especially as information becomes available in huge quantities from a multiplicity of And a lack of data literacy can lead to the misinterpretation, or misrepresentation of the facts. Someone who wants to win an argument using data can usually do so. This is not to say that there is no proper use of data mining, as it can in-fact lead to surprise outliers and interesting analyses. Ethics in statistics are very important during data representation as well. Even in the hands of someone benevolent, data can be misinterpreted in dangerous ways. All viable data sets, even in their disparate formats. Data interpretation is critique and determination of information significance. “I like data because it helps me win arguments” – Never has a phrase better revealed someone who doesn’t get value from data — Andrew Anderson (@antfoodz) January 6, 2015 Data dredging is a self-serving technique often employed for the unethical purpose of circumventing traditional data mining techniques, in order to seek additional data conclusions that do not exist. Streaming data from social media feeds (not filtered). Misinterpretation of Study Data—Reply Michael R. Wilson, MD, MAS; Brian D. O’Donovan, MS; Joseph L. DeRisi, PhD To the Editor The recent Wilson et al study 1 reported that next-generation sequencing served as a diagnostic tool for neurological infections. Hold on. Unstructured data from research studies (format varies between text, audio & video). research, across research designs and is difﬁcult to elim-inate; second, bias can occur at each stage of the research process; third, bias impacts on the validity and reliability of study ﬁndings and misinterpretation of data can have important consequences for practice. Data selection and bias. This happens both in pure and social sciences. The controversial study that suggested a link between the By obscuring data or taking only the data points that reinforce a particular theory, scientists are indulging in unethical behavior. You might think the next action is loading all of the data & starting on queries. One can create an extremely robust model where the results […] Numbers don't lie but their interpretation and representation can be misleading.