Outliers Significant Role in Statistical Calculations

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Outliers Impact
Statistical calculations are made to ensure that the set of data perfectly presents the concept that was being researched on. Therefore, the researcher has the obligation of making precise calculations to ensure that they do not contain data which could compromise the effectiveness of the results. Outliers are examples of the values that could have an impact on statistical calculations. An outlier is considered to be a value that is very different from the other set of data. Research indicates that the presence of outliers in a given set of data can have a huge impact on the mean and standard deviation. Therefore, ways have been devised to ensure that outliers are mathematically eliminated from any set of data. Hence, outliers have many impacts on statistical calculations.
An Outliers has a limited impact on the median of data as compared to the impact that it has on the mean. The median is the preferred measure of the data's central tendency in the case of an asymmetrical distribution. Therefore, the impact created by the outliers on the mean and the median result to an effect on the error in a given set of data. Therefore, in such a case, when the data is plotted, there is a huge deviation which could not be seen in the case whereby the outliers were absent. The smaller the deviation of a given set of data, the more effective the set of calculations is. As a result, statistical calculations have to be done to eliminate outliers in any given set of data. The elimination of the outliers increases the effectiveness of the data in representing the concept that was being measured. Also, the median is most preferred to the median because it is less affected by outliers hence presenting perfect data.
On the other hand, the mean is highly affected by outliers because it includes all the values in the distribution. Given the fact that the mean is used in the calculation of the standard deviation, then it follows that the outliers also have an impact on the standard deviation. For instance, in the case whereby a set of data ranges from 50 to 65, then its mean value will be different from that of the similar data but with a value such as 80 in the data set. An outlier on the extreme higher side of the data is known to increase the mean value while that on the lower extremity is known to reduce the mean value. Since the mean of the numbers is the estimated average, then it should be a value which is closer to most of the data. Therefore, this calls for the researcher to eliminate the outliers because, in the real sense, it provides a mean value which is not reasonable.
Outliers play an important role in statistical calculations because they represent the numbers outside the Box Plot. They are the numbers on the upper and the lower fence....