How are statistics being applied in computer science to evaluate accuracy in research claims?
As a graduate student in computer science, who has exposure to research in fields other than computer science, and whose research group works in an area of computer science where statistics can be fruitfully applied, I can offer my experience; your mileage may vary.

In general, even the most well-meaning scientific research can fail to rigorously apply statistical analysis to results, and it is my experience that this does not always preclude papers including such poorly-analyzed results from being accepted for publication. The area in which my group operates is mainly in distributed computing and high-performance computer architecture. Often, research involves experimental designs the performance of which cannot easily be understood analytically in the required detail. As such, empirical results are often used as evidence for claims.

Clearly, experiments should be design - and results analyzed - in such a way as to provide some confidence that the results are statistically significant. Most of the time, this is not done, even in some of the most important venues. When statistical analysis is applied, it is almost never rigorous in any meaningful sense; the most one typically sees (and one is glad to see it!) is that an experiment was repeated n times, for some arbitrarily-chosen n, where typically $1 &lt; n &lt; 5$. The selection of error bars (if any are indicated) seems to be mainly a matter of personal preference or taste.

In summary, no, it's not just you; and it's not just software engineering. In general, based on my experience, several areas of computing research seem to err on the side of not doing enough. Indeed, it might be even be detrimental to the viability of a submitted paper to dwell on statistical considerations. That's not to say that I find the situation satisfactory; far from it. But these are my impressions. For instance, you may take a look at section 5 of this paper, which was presented at Supercomputing 2011, one of the most high-profile conferences in the area of high-performance computing. Specifically, take a look at some of the discussion of results in section 5, and see whether you arrive at the same conclusions that I do about the rigor of statistical analysis of experimental results.

More generally, this shortcoming may be symptomatic of a condition in some areas of computing to publish more papers rather than fewer, to target conferences rather than journals, and to emphasize incremental progress rather than significant and fundamental improvements in understanding. You might consult this article, which provides valuable insight along these lines.