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  • Hands-On Data Science with R
  • Vitor Bianchi Lanzetta Nataraj Dasgupta Ricardo Anjoleto Farias
  • 243字
  • 2021-06-10 19:12:31

Measures of central tendency and dispersion

If you care to tackle a problem using the statistic's arsenal there are two tools to begin with: measures of central tendency and measures of variance. This is the starting point for most of the statistical problems. These measures are used in a thing that some would call descriptive analysis. A well done descriptive analysis may be all that you need, depending on the problem you have at hand. Think about the force continuum (and don't go straight to the Megazordstart small).

Central tendency (or average) means typical/middle value from a distribution. This is an abstract concept and we can't really measure it. Yet there are estimates that try to translate this abstract concept into an actual measure. Arithmetic mean, median, and mode are all widespread and consolidated attempts.

Even if you got yourself stuck with a more complex problem, there is still room for descriptive analysis. A carefully drawn analysis will both appreciate and validate all the good work coming afterward. This section will introduce you to the measures of central tendency and variance. It will show you what they are made of as well as how to obtain them using R. Although base R is more than enough for this kind of action, there are packages that are able to do more with less—we will visit some of them.

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