Hopefully somebody on the board can help me out...
Anyway at work I'm doing research in Cardiology, and I don't know why but my boss assigned my first study to be - "does the lunar cycle have an effect on heart attacks".
So basically I maintain a database of all patients that enter the CCU (cardiac care unit). I filtered it so only the heart attack (MI) patients remained. Then beside their admission date (i.e. date of MI), I put a rating in another field which meant how close they were to the closest full moon (that's all I'm really looking at).
The ratings went from -14 (14 days before the closest full moon) to 0 days (the day of the full moon) to +15 days (15 days after the closest full moon). The +15 only happens about half as much as any rating from -14 to +14 though, so I adjusted all the results in the end by dividing the frequency by how many times each rating occured from the time period I analysed.
Anyway in the end, I have a table of simple data, basically the frequency of MI's for each rating (and there was no correlation in case you're interested ).
So from here I have to show that it isn't statistically significant, etc...
What kind of test do I run the data through?
:-\
I'm desperate
Anyway at work I'm doing research in Cardiology, and I don't know why but my boss assigned my first study to be - "does the lunar cycle have an effect on heart attacks".
So basically I maintain a database of all patients that enter the CCU (cardiac care unit). I filtered it so only the heart attack (MI) patients remained. Then beside their admission date (i.e. date of MI), I put a rating in another field which meant how close they were to the closest full moon (that's all I'm really looking at).
The ratings went from -14 (14 days before the closest full moon) to 0 days (the day of the full moon) to +15 days (15 days after the closest full moon). The +15 only happens about half as much as any rating from -14 to +14 though, so I adjusted all the results in the end by dividing the frequency by how many times each rating occured from the time period I analysed.
Anyway in the end, I have a table of simple data, basically the frequency of MI's for each rating (and there was no correlation in case you're interested ).
So from here I have to show that it isn't statistically significant, etc...
What kind of test do I run the data through?
:-\
I'm desperate