I have collected employee turnover rates over the year. The attrition rates are as such:
Month | Attrition Rate |
---|---|
Jan | 2.23% |
Feb | 1.40% |
Mar | 2.99% |
Apr | 1.43% |
May | 1.72% |
Jun | 1.15% |
Jul | 1.64% |
Aug | 1.60% |
Sep | 2.00% |
Oct | 2.15% |
Nov | 1.08% |
Dec | 1.30% |
I'm comparing these attrition rates to the industry benchmark rate of 1.44% by using a One-Sample t-test.
Is this correct, and if not, what is the best way to confirm if the Mean Attrition Rate in this year is significantly higher or lower than the industry benchmark?
I need to be able to make a statement and say that: "Year XXX has an employee attrition rate of X.X%, and this is (not) significantly higher/lower that the industry benchmark of X.X%"
In addition, if I were to compare Mean attrition rate of this year versus the previous year, is it correct for me to do a paired samples t-test, or should I do an Independent 2 Sample T-Test?
EDIT
After giving this more thought, I'm thinking that if I were to test the means of percentages using the the t-test, what I am comparing is effectively the proportion, between 0 to 1, as a whole whether the proportions are significantly different...
However if I tested just the actual turnover headcount figures, I would be comparing the mean turnover headcount of a group of months vs (let's say for example) the mean turnover headcount vs a previous month... This would be a more direct measure of turnover, but because it's not a proportion, it's less meaningful because it's not based on any thing. I wanted to compare turnover rates because turnover rates = Leavers / Total Employees. The denominator here plays a significant role in moderating the turnover rate.
Any advice/thoughts/comments?