Comparing the hospital stay of two surgical methods I'm a complete novice in statistics, but while doing my first publication in medical research my advisor gave me the task to analyse a dataset. So the problem:
I'm comparing the time spent in a hospital after surgery between two surgical methods (robotic assisted and traditional open technique). The dataset is quite large (7960 cases). Basically I'm comparing two groups (which surgery = nominal data) by the days spent in hospital (scale), while taking into account about 7 other nominal and scale variables (eq. lymphnode dissection, was the surgery done in an university hospital, the year of the surgery and so on).The point of the study is to see weather the chosen method has an effect on the post op days and how big is that effect. 
Which statistical method should I use? Preferably one that can be done with SPSS with some practice.
 A: This sounds like a job for survival analysis. In this case, "survival" is the number of days to discharge, and shorter "survival" is better. If the appropriate assumptions are met, a Cox proportional hazards regression could evaluate the open/robotic-assisted variable of main interest while accounting for the influences of your other covariates.
A: This is standard ANCOVA or general linear model if you'd rather call it that. Since times tend to be skewed, you should examine the distribution of the residuals and, perhaps transform the data using log or something similar. In SPSS I believe it is under General Linear Model but I'm not sure because I don't use SPSS.
A: I agree with @MissMonicaE.  A logistic regression should work for you, just use the group as the dependent variable and put all the others in as covariates. See the link below for step-by-step instructions in SPSS, and help interpreting and reporting the results. 
https://statistics.laerd.com/spss-tutorials/binomial-logistic-regression-using-spss-statistics.php
