Measures of central tendency: Average or mean: mean, colMeans, rowMeans
 Median: median
Measures of dispersion:  Variance (sample): var
 Standard deviation (sample): sd
 Median absolute deviation (sample): mad
 Interquartile range: IQR
 Range: range
Other useful measures:  Totals: sum, colSums, rowSums
 Extrema: max, min, range
Characterization of the distribution of values:  Histograms: hist
 Boxplot: boxplot
 Quantiles: quantile
Probability distributions:  Get a list of the distributions supported by R: help(Distributions)
 The probability distribution functions usually have four different forms (e., g., dnorm, pnorm, qnorm, and rnorm). The four variations correspond to the heights of the probability distribution, the heights of the cumulative probability distributions, the quantiles (working backwards from probabilities), and random values drawn for the distribution.
Variable relationships:  Linearly related: Vector variables x and y are linearly related if y_{i} = m * x_{i} + b (When plotted against each other as ordered pairs the points fall on a line.)
 Covariance measures how linearly related two variables are: cov(x, y)
 Correlation is a normalized measure of how linearly related variables are. The values of correlation are between 1 and 1. A value of zero indicates no relationship. cor(x, y)
