simulation

Understanding whether a variable’s missingness from a dataset is related to the underlying value of the data is a key concept in the field of missing data analysis. We distinguish three broad categories: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR).

In a first semester probability course, students encounter combinatorics and point estimates such as the mean and median of a data set. A common example is the low odds of winning the lottery.

A look at the distribution of age at death based on social security mortality tables to see how long we can expect to be in retirement for.