Efficient data analysis requires more than just static use of analysis methods. Thanks to comprehensive knowledge of all current processes, creative and goal-orientated approaches, an understanding of what is possible, avoiding errors and, last but not least, by heeding the most important quality criteria in applied statistics, namely utility, it is possible to maximise the findings gathered. In doing so, it is important, however, not to lose sight of economic requirements.
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