Looking, like before, at number of missing answers (which seems like an awful good proxy for how much time one puts into the survey), the people who were right on the first question answer 1 more question but that small difference doesn't reach statistical significance:

R> lw <- read.csv("2012.csv")
R> lw$MissingAnswers <- apply(lw, 1, function(x) sum(sapply(x, function(y) is.na(y) || as.character(y)==" ")))
R> right <- lw[as.character(lw$CFARQuestion1) == "Yes",]$MissingAnswers
R> wrong <- lw[as.character(lw$CFARQuestion1) == "no" | as.character(lw$CFARQuestion1) == "Cannot be determined",]$MissingAnswers
R> t.test(right, wrong)
Welch Two Sample t-test
data: right and wrong
t = -1.542, df = 942.5, p-value = 0.1234
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-2.3817 0.2858
sample estimates:
mean of x mean of y
16.69 17.74

(I'm not going to look at the other questions unless someone really wants me to, since the first question is the one that would benefit the most from some extended thought, unlike the others.)