# Is it logical to look for a correlation between average and percentage?

I have a simple question. Can one look for correlations between percentage and average ? For example, percentage of unemployment and average salary. Or shoul I use total numbers instead ? If I look for a relation between percentages and average I get significant correlation, but between totals data is not significant.

• Usually, when looking for correlations, it is an attempt to define cause and effect relationships. I can find correlations between the date of the year and my check number, but the fact both increase sequentially is rather expected. There is also a significant correlation between pirates and global warming, but there is (to my knowledge) no cause and effect relationship between the data. Mar 6, 2017 at 8:14
• @subhashc.davar My variables are percentages of unemployed people in state every month and average salary of employed people in state every month. So I have unemployment data from bureau of statistics USA and average salary is calculated from randomly selected 10K people in that state. Mar 6, 2017 at 9:24
• @subhashc.davar Correct Mar 6, 2017 at 9:44

I'd be really uncomfortable with a correlation between a(n average of) continuous variable and a percentage, because the percentage is bounded by $[0,100]$. So if the percentage is near these boundaries, the relation (i.e. correlation) between the two is bound to be non-linear. A more suitable way of associating one continuous and a categorical variable is, for example, through regression.
• Most often a percentage is calculated by grouping in some way (e.g. the proportion of men out of the total sample). I assumed this is what you meant. But I must admit, sometimes a percentage is used to show change from a certain baseline point (e.g. my income has changed by 150%). This second case is slightly different because in this case the percentage is bounded only on the lower side ([$0,∞]$), but still the problem of non-linearity remains, especially if you include '100%' as the neutral (no-change) point.