Abstract
For a proper understanding of many informetric concepts, a basis in statistics is indispensable. For this reason, this chapter introduces both descriptive and inferential statistics. In the first part (descriptive statistics), we introduce the difference between nominal, ordinal and interval scales, and the relation to bar diagrams and histograms. Various measures of central tendency. measures of statistical dispersion are explained, and two procedures for determining percentiles (quantiles) are covered in this section. We then turn to the graphical representation in a scatter plot and ways of finding the best fitting line (linear regression) in the resulting cloud of points. Inequality in causes and effects can be visualized and quantified using the Lorenz curve and Gini index. The second part (inferential statistics) introduces the normal distribution and the z-score. The chapter closes by providing two nonparametric methods for hypothesis testing the chi-square test and the Mann-Whitney U-test.
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