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Likes and dideerecnes of computing variances

Likes and differences of computing variance Variance is one of the available statistics for describing data sets and it defines the square of mean deviations of each data point from the mean of the data. Differences between data points, which can be understood as the distance between data points, are another descriptive approach to data analysis. This paper seeks to explain that computing a variance of the same numbers is the same as analysis of the numbers’ differences.
The definition of variance offers a basis for understanding the statistic’s relationship with differences between numbers. Having been defined as the square of mean differences between each number in a data set and the mean of all the numbers in the set, the variance is a derivative of differences between the same numbers. Computing the variance of a data set is therefore equivalent to analyzing the difference between the same numbers (Wegner, 2010). The definition of variance as a measure of dispersion also explains the relationship between the variance and the difference between points. A data set with a higher magnitude variance, for instance, means that data points in the set are far apart from each other, a factor that indicates greater variation from the mean. The gaps between the data points however defines the differences between the points and this means that computing the variance and analyzing differences between data points generate the same understanding on distribution of data in the set (Madrigal, 2012).
The two measures therefore develop the same understanding and this paper concludes that computing the variance of the same numbers is like analyzing the numbers’ differences.
References
Madrigal, L. (2012). Statistics for anthropology. New York, NY: Cambridge University Press.
Wegner, T. (2010). Applied business statistics: Methods and excel-based applications. Cape Town: Juta and Company Ltd.

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