Other Statistical Forms
Linear regression is
certainly not the only form of statistical analysis available. Essentially,
some form of statistical analysis exists to assess the links between
any variables, no matter what they might be. For example:
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Whereas linear regression of the form discussed so far generally requires dependent variables that are continuous (interval or ratio in data), other forms of regression can analyze dependent variables that are ordinal or categorical (e.g. where you wish to analyze actual employee turnover, which is a binary variable having the values 0=stayed at the organization and 1=left the organization).
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In a similar vein, categorical independent and dependent variables can be related together.
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Special statistical techniques exist for analyzing change in variables over time (time series), variables that contain spatial and temporal aspects (geographic information data) and many other types.
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Sometimes you want to analyze patterns in data with no particular dependent variable specified (interdependence techniques like factor and cluster analysis).
The statistical universe
is vast! However, you will generally find that the thinking and often
the interpretation of such statistics is similar to linear regression.
This course will not cover many other statistical analysis forms in
detail, but the skills developed in this chapter will make it easy
for you to assimilate new techniques if necessary.
Last updated: April 18, 2017
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