I agree that a "typical" biologist (if such thing really exists) is generally not skilled in CS nor, very scaringly, in statistics.
My experience is that most biologists think of these things as burdens that do not really interest them and only get to do some basic statistics (most biologists would sort of know what a t-test or an ANOVA is, although they most probably won't master the statistical theory behind it) before writing a paper, so that they can put the little stars on their graphs.
However, if you go into fields like neuroscience (which I count as biology, I am not sure why you seem to imply it is not) then you start meeting people who know quite a bit of CS. Generally you either have these hybrid mathematician/statistician/programmer/math-y guy/biologist or you have biologists working together with more CS people.
In my last lab, for instance, we used to have a physicist and a programmer to help out with biological data analysis.
Furthermore, if you're into imaging, then there may be a lot of programming needed for 3D reconstruction, image segmentation, particle tracking, etc. etc. Although there is some fairly impressive off-the-shelf software out there for the most common tasks, as soon as you want something a bit more specific you're better off programming it yourself, or finding a collaboration with some computer scientists.
I would say that as a biologist it is important to understand these things, but not necessarily to be able to actually perform them, as you can rely on CS specialists/bioinformaticians to do that for you. However, it is very important for the biologist to understand what the bioinformatician does, and vice versa, as communication is obviously of great importance in these situations.