Apologies for the noob question. After a day on Google and Wikipedia I still can't quite work out what to do. So here I am.
A small private healthcare clinic in the UK has asked me to look at their patient appointments data. Patients hear about the clinic from various sources (Google, word-of-mouth, leaflets, etc etc). Plotting [patient numbers] against [number of appointments per patient] appears to reveal intriguing patterns in patient "loyalty":
The X-axis is each source:
- saw the clinic while visiting another business in the same building
- recommended by another patient
- friend of the clinician
- saw our street sign
- etc etc etc
The pink bars show total number of patients per source. Not too surprising that Google is up high, as is the street sign. But intriguingly the patients from Google/street-sign only come for 3 or 4 appointments - see the blue bars - whereas the patients to the left from sources including word-of-mouth appear to be more "loyal", visiting for a higher mean number of appointments.
I'm curious if this is a real effect, or a glitch in the smaller sample sizes of the left-most data. The left-most 4 sources have sample sizes of 7, 12, 6 and 9.
Exactly which test should I use to determine significance here? I have month-by-month totals for each source for the past year, like this:
As you can see, I've started calculating standard deviations and standard errors. However I'm a little stuck now. Should I be using ANOVA here? If so, how exactly?
I should add I'm a novice at this so feel free to use small words and type slowly. I've looked through "similar questions" but I'm still no wiser.
Many thanks for your help.