Evidence-based scientific researchers mainly present results as statistical data or in form of graphs. Statistics is the technique, which quantitatively interprets data. Data represented is in form of variable numbers which aid in calculation of probability and error of results of a study . Statistical data is mainly biased or contain false variables of results. The huge margin of error makes statistical interpretation of data to be false. Variables may project certain outcome which is used as supporting evidence for nursing study. The changing numbers of the data collected mainly depend on various factors such as source of data, method of data collection, personal attributes among others. The collected data is represented as graphs to explain certain phenomenon. If error occurred in the process, the information generated from the data will be false, thus misrepresentation.
Graphical representation of data is dictated by calculations made and formulas used. High bias percentage and errors in calculations results to wrong interpretation of information . A good example is depicted by sampling technique used in a specified population to carry out evidence-based research. Researchers use clinical trials of a certain drug to draw conclusions of the efficacy of the drug. The data collected acts as true representation of the entire population. This may result to false information as drug efficacy is determined by various factors such as location, sampling technique among others. The margin of error in conducting such clinical trials varies. If wrong data is used to project outcomes of a study, the people reading the information will be misguided.
Work cited
Hardin, James & Phillip, Good. Common Errors in Statistics (and How to Avoid Them). New
York: John Wiley & Sons, 2012.
Kuby, Patricia & Robert, Johnson. Elementary Statistics. London: Cengage Learning, 2011.
