Which variable is not a good candidate for PROC MEANS analysis?

IDnum

The choice of IDnum as a variable not suitable for PROC MEANS analysis is based on its nature as an identifier rather than a quantitative variable. PROC MEANS is designed to compute summary statistics such as mean, standard deviation, minimum, and maximum for numeric variables. Therefore, it is most effective when applied to continuous data that can provide meaningful statistical interpretation.

IDnum typically represents a unique identifier for each observation, such as a customer ID or a unique record number, and does not contain meaningful numeric data that contributes to summary statistics. Instead of providing insights into distributions, averages, or other statistical measures, it merely serves the purpose of distinguishing one observation from another.

In contrast, Age, Height, and Weight are all numeric variables that convey quantitative information and can meaningfully contribute to descriptive statistics in PROC MEANS. These variables are continuous in nature and provide insight into the data set's characteristics, making them suitable candidates for this analysis.

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Age

Height

Weight

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