I have a problem to solve – I feel that a team is taking unplanned leaves just by extending their planned leaves.
For example, if someone has planned and applied for vacation on 9th and 10th of March then they are sending an email or text message saying they will be on leave for 13th also. I have seen this happen for over last 6 months from a majority of the resources in a team.
I have 6 months worth data for this in the below format. There are four columns.
Resource Name | Planned Leave Date | Unplanned Leave Date | Is Adjacent to Planned?
My Business problem is that I want to prove that there is an association between the unplanned leaves and planned leaves.
I do not know what I should use to prove this statistically – Chi Square Test for association (because my data is discrete?)
OR should I look at it as binary data (The “Is Adjacent to Planned Leave?” flag) and just go by the Mode? i.e., the more “Yes” to that flag proves that the team members are taking unplanned leaves by extending planned leaves. They should avoid this and plan better next time so the delivery is not impacted.
How do I go about this? Any pointers please?
Chi squared is a good place to start. Also, see if you can graphically display your data so you’re not just quoting p-values. :)
not just quoting p-values
haha that is the best advice ever. I remember reading, what p-value tells us is only the statistical solution. We need to translate that into the Business solution.
May I know why you suggested for Chi Squared over the simple mode?