CROSS-SECTIONAL MODELS

In all our statistical work to date, we have been dealing with analyses of time-ordered data, or time series: the same variable or variables observed and measured at consecutive points of time. Usually but not necessarily, the points of time are equally spaced. Time-ordered data are very often pertinent for total quality; for example, we need to know whether our processes are in statistical control or whether they are being affected by, say, trends or special causes. We need also to evaluate the effectiveness of interventions aimed at improving our processes and to assure that we are holding the gains from effective interventions from the past. But not all data are time-ordered. There is also a type of data called cross-sectional data, where we are dealing with information about different individuals (or aggregates such as work teams, sales territories, stores, etc.) at the same point of time or during the same time period.

The dropbox folder contains exercises, research papers and industry cases that will be covered.