Abstract
Descriptive statistics summarize information. In this chapter, we review two kinds of descriptive statistics: measures of central tendency and measures of dispersion. Measures of central tendency are meant to summarize the profile of a variable. Although widespread, these statistics are often misused. I provide guidelines for using them. Measures of dispersion are complementary: they are meant to assess how good a given measure of central tendency is at summarizing the variable.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
It would make little sense to say that mild agentivity is twice as less as high agentivity.
- 2.
With par(), you can set up graphical parameters. A layout with two plots side by side is specified using mfrow(). The line par(mfrow=c(1,2)) means “multiframe, row-wise, 1 line × 2 columns layout”. As a result, the two plots are organized in one row and two columns.
- 3.
As a rule, the smaller the data set, the more sensitive it is towards extreme values.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this chapter
Cite this chapter
Desagulier, G. (2017). Descriptive Statistics. In: Corpus Linguistics and Statistics with R. Quantitative Methods in the Humanities and Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-64572-8_7
Download citation
DOI: https://doi.org/10.1007/978-3-319-64572-8_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-64570-4
Online ISBN: 978-3-319-64572-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)