I have a sample size of 4 or 3. Each sample is the difference between climate variables (Temperature, vapor pressure, wind, solar radiation, etc.) under two different conditions (variable value inside - variable value outside. I cannot assume normality. My sample and population are continuous. I want to know if these differences are significantly different from 0.
I would like to test if the mean is significantly different than 0. I am considering using a t-test with mean = 0 for the null. But this test, assumes normality.
The other test I am considering is the Wilcoxon rank-sum test, but it looks like it only compares two samples. Can I use it to test against a mean of 0?
What other tests are available for small sample sizes where parametric assumptions are not necessarily met?
Edit Purpose of my study
I have weather stations collecting data inside and outside low-tech greenhouses. I am testing to see if the differences between the weather station data inside and outside is statistically significant.
Because I have an unequal number of replicates inside and outside the greenhouses, I calculated the difference for each variable between each weather station inside each greenhouse and the weather station outside. I was hoping to test the significance of the differences from zero rather than the original weather station data. However in order to use the t-test, I need to transform some of my data or find another test.