DSPA Chapter 2 Data Management in RIn this chapter, we will discuss strategies to import data and export
results. Also, we are going to learn the basic tricks we need to know
about processing different types of data. Specifically, we will
illustrate common R data structures and strategies for
loading (ingesting) and saving (regurgitating) data. In addition, we
will (1) present some basic statistics, e.g., for measuring central
tendency (mean, median, mode) or dispersion (variance, quartiles,
range), (2) explore simple plots, (3) demonstrate the uniform and normal
distributions, (4) contrast numerical and categorical types of
variables, (5) present strategies for handling incomplete (missing)
data, and (6) show the need for cohort-rebalancing when comparing
imbalanced groups of subjects, cases or units.
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