I am analyzing some stats for a paper I am writing. I have statistics help available through my faculty but am not there for a couple of months so hoping you can help out.
n = 463, 2 patient groups( <70 & >= 70 years). Using SPSS.
I have assessed a whole bunch of stats using Pearson's $\chi^2$ test - They are categorical such as Smoking History (T/F), Smoking Current (T/F), BMI>30, Diabetes,etc. So far so good (Unless anyone can tell me if this is an inappropriate test?)
I have more variables such as Pre-operative Creatine, ICU hours stay, etc., which are not normally distributed (I used to know how to test for normality 'properly' but I have just drawn Q-Q plots and seen if they are on the line and they aren't. My intention was to use student's t but my rusty stats knowledge tells me I can't now because they aren't normally distributed.
In many aspects I am using the statistical methods of a friend that wrote a similar paper using a similar dataset, and for his continuous variables he used Kolmogorov-Smirnov but I'm not sure if he just used this for normality. He then says that he used Kruskal-Wallis to assess these variables but I can't work out why this is appropriate.
Would someone mind explaining to me if these tests are appropriate for comparing these samples?