layzwombat

Another thing to note about the statistical packages is what bignose stated: bottom line, if you do not know what a test is doing (ie. test of location - mean or median, variance, etc) you probably won't know the assumptions required for the test to be run in the first place. That being said - if you do, most programs will give you the proper information in the output as long as you know what to look for. Example: If you run an ANOVA test (equal variance assumption - others should be worked out in the study design) SPSS will use a Levene statistic to test before it gives you the results from the ANOVA - if Levene fails, than obviously the ANOVA is irrelevant, and you have unequal variances (Try a Welches ANOVA in this case). I believe SAS uses a Folded-F test to do the same thing. In my opinion the understanding a statistical package is a great compliment to the skill, and it looks good on a resume. I would have to recommend SPSS as it is becoming more common, and easier to use than most packages. It also has an interface similar to an excel spreadsheet.

I am certainly not an expert in this area, but this may be a note that will help. If you were to go into excel and use the random number generator - it will give you random numbers. However, if you are in a classroom and you instruct the class to all do the same operation in the random number generator (same mean, std, etc.) the entire class will get the same values. Is that what you are getting at?

Basically any analysis requires statistical evidence. Depending on the data, you have to run a certain set of tests if say you have 3+ samples. You absolutely can do these by hand, if you have the time and patience, but a statistical package will make this much easier. SAS and SPSS are fairly common in my area (SPSS being much more user friendly), but I've noticed that text books like minitab - and I'm not sure why.

Plants use a ratio of C:N:P and I actually forget the ratio at the moment (not important to answer), but you can use the isotopes to measure which fertilizer would closest match your crop ratio. An example of this would be if you were growing soy beans, your fertilizer should probably have zero nitrogen since legumes fix their own nitrogen, and thus you can lower your environmental damage.