Variables can be differentiated by two characteristics. The first characteristic is the scale of the variable (i.e. the values that the variable can assume). The second is the role that the variable fulfills in a statistical model.
Measurements scales of variables Variables can be on the following scales:
Quantitative variables: Variables indicating numeric values for which pairwise differences are meaningful. Categorical variables: Variables representing a discrete set of groups.
R is a great tool for working with distributions. However, one has to know which specific function is the right wrong. Here, I’ll discuss which functions are available for dealing with the normal distribution: dnorm, pnorm, qnorm, and rnorm.
Two of the most commonly used statistical measures are the mean and the median. Both measures indicate the central value of a distribution, that is, the value at which one would expect the majority of data points to lie. In many applications, however, it is useful to think about which of the two measures is more appropriate given the data at hand. In this post, we’ll investigate the differences between both quantities and give recommendations when one should be
preferred over the other.
