Descriptive statistics

Descriptive statistics are a set of technologies (ie, formulas and procedures) used for describing mathematical properties of a database (eg, factor analysis of all variables in a dataset) or part thereof (eg, central tendency of particular variables).

As a dataset is always specific to a particular group, descriptive statistics are also bound to such particular group. This means that descriptive statistics can always say something about such group, independently of whether the data is usable further or not. That is, these statistics always 'describe' properties of the particular group under research (eg, of a sample). They are often used for assessing the quality of the data in the dataset and, thus, for ascertaining if it is appropriate to continue further into using inferential statistics2.

Illustration 1 offers a snapshot of typical descriptive statistics.

Illustration 1. Descriptive statistics
Type of analysis nominal ordinal interval
Central tendency mode median mean
Dispersion modal dispersion SQR, SPR standard deviation
~ variation ratio IQR, IPR variance
Graphs pictograph stem-and-leaf histogram
~ bar graph line graph error bar
~ pie chart box-and-whisker
Asymmetry --- rank skewness skewness
Peakness --- --- kurtosis
Location --- percentile z-scores
Type of analysis nominal ordinal interval
Correlation --- rho r
Type of analysis nominal ordinal interval
Grouping --- cluster analysis principal component analysis
~ --- --- factor analysis
1. full reference in the following format AUTHOR (date work).Title. Reference location, date publication. ISBN/ISSN.
+++ Notes +++
2. When descriptive statistics are used on a whole population it is unnecessary to go any further into inferential statistics, as there is no need to infer mathematical properties of a population whose mathematical properties are already known.

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Wiki of Science - Inferential statistics
This page provides access to other statistic technologies used for making inferences from a sample to a population.

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