Academic Writing: The Cross with Statistics

Academic Writing: The Cross with Statistics

While scientific writing can be mastered for most young academics despite all the hurdles, it often looks different when it comes to using statistical methods. But whoever faces up to this task can achieve a lot.

At the latest when considering the sum sign at the beginning of a long formula, some startle together. For where the domain of mathematics, statistics and stochastics begins, the classical sociological, psychological, political or economic knowledge that feeds on long texts no longer helps: without an understanding of statistical methods, empirical observations can hardly be reduced to one bring scientific form and prove. Also, people without this understanding will hardly be able to expose the many tricks that politicians and lobbyists use to manipulate moods. A study of statistics is therefore always worthwhile.

Anyone who struggles with the statistical methods of empirical social research, should first look in the circle of fellow students: In small learning groups and equipped with the right literature, the mean and modal value, the median, the variance, and the quantile distance, the span and determine the standard deviation more easily than alone.

In addition, ghostwriters also offer statistical evaluations and consultations: even some of the skewed arguments or statistical inconsistencies have been corrected by the writing helpers.

Whether the subtleties of higher statistics are to be investigated with SPSS, or only a few smaller surveys are to be evaluated with Excel – ghostwriters can be used as a “fire brigade” in case of emergency, if a bigger problem opens up shortly before the planned delivery date.

In order to convince statistics, statistics have to be meaningfully integrated into the context of the work: the mere application of the methods does not in any way replace the lack of understanding of the theory and hypothesis formation. Especially in these areas ghostwriters score because of their extensive experience. So instead of being a purely academic style exercise, the evaluation of statistical data is integrated into the argumentation sequence of the thesis.