Least Significant Nibble

You will never get read without an eye-grabbing headline. My beef with Schema arose while working through a set of programming problems that are published online. I was interested in using those problems to familiarize myself with the idioms of Scheme and Haskell , with which I am less familiar. The exercise in question asks for the sum of all Fibonacci numbers that do not exceed 10000 and are divisible by 2. For the purposes of this post, the Fibonacci sequence is defined by a recurrence relation: \[ \begin{align} F(0) &= 0 \\ F(1) &= 1 \\ F(n) &= F(n - 2) + F(n - 1). \\ \end{align} \] In an imperative language such as C , this problem can be solved with a program similar to the following one. The logic of this program mimics how a person might solve the problem with a pencil, paper, and a pocket calculator: it keeps a running total of the even Fibonacci numbers as they are computed. This is the kind of code I could write in my sleep, which is why I am interested in

Survey data is well known to be an imperfect measure of the truth. The many pitfalls of survey data mean that the numbers must be taken with some healthy skepticism. Evidence-free assertions that black people are three times more dishonest than white people in answering surveys about drug use do not a healthy skepticism make. @voxdotcom These figures based on self-reported drug use are notoriously unreliable. I thought it was your job to report "context"? — Billy Chav (@billy_chav) February 5, 2015