The point is that sophisticated multivariate analyses such as factor analysis with Varimax rotation or Cox Proportional Hazards Regression do not alert you when someone entered a patient’s body temperature on Wednesday morning as 986 degrees instead of 98.6 degrees. Then you can take steps to correct data entered in error, or to adjust your decision rules if necessary, or even to replicate the experiment if it looks like something might have gone wrong with the methodology. No matter what the cause, if your data set contains any unexpected values you want to know about it. The reasons vary from the mundane (someone entered an impossible value for a variable) to the technical (different sample sizes accompanying different variances).Īny of those events could happen, whether the source of the data is a sales ledger, a beautifully designed medical experiment or a study of political preferences.
Regardless of the sort of analysis you have in mind for a particular data set, you want to understand the distribution of the variables in that set. Analyzing One Factor by Another: The Contingency Table
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