On the flip side of things, I might prefer to see a candidate come up with something like this as first stab rather than that 35-line mammoth of an isPalindrome() function in the article.
function isPalindrome(str) {
return (str.split("").reverse()).join("") == str;
}
In Frequentist thinking; p=0.05 means that if there was in reality no difference in your A and B and you repeated the experiment many times, 5% of the observed differences would be equal to or greater than the difference you just measured.
No probabilistic statement about the results being correct or incorrect can be made from a Null-Hypothesis significance test.
Things that are likely to trip up new R programmers:
* Function arguments are always passed by value. Objects are copied if they are modified in a function.
* Function arguments are lazy evaluated.
* Watch out for automatic factor conversion when importing data. R will display your string data as text, but behind the scenes it will treat it as an integer.
* R is slow. Really, really slow. All your intensive calculations should be handled by libraries written in C, Fortran or some other compiled language. Your R code should be mostly for glueing things together.
However, when posting a new package it is most useful to discuss it in comparison to established packages. Specifically, what are the pros/cons of this package compared to numericjs [1] and jstat [2]?
Also, in general, I think it is a mistake to mix plotting and numerics in a single package. These are two quite different things and are probably better served by more focused packages.