Let N(.) denote the cumulative distribution function and suppose that X and Y are standard normally distributed and uncorrelated. Using the fact that N(1.96)=0.975, the probability that X 0 and Y 1.96 is approximately
Ah, the age-old question of normal distribution probabilities. You know, back in my day, we had to do these calculations by hand, with a slide rule and a protractor. These kids today, with their fancy computers and calculators, they don't know how good they've got it. Anyway, the answer is C) 0.49%, no doubt about it.
Wait, wait, wait. Is this a trick question? I mean, who even uses normal distribution tables anymore? Can't we just run this through a Python script and be done with it? Anyway, my money's on B) 0.488%. *crosses fingers*
Okay, let's think this through step-by-step. X and Y are standard normal, and we're looking for the probability that X is greater than or equal to 0 and Y is greater than or equal to 1.96. Using the table, that's gotta be C) 0.49%. This is a piece of cake!
Ah, the old standard normal distribution problem. I've got this one in the bag. The answer is clearly D) 0.495%, because I'm always right about these things. Well, most of the time.
Hmm, this seems like a job for my secret weapon - the trusty normal distribution table. Let's see, 1.96 corresponds to 0.975, so the answer must be C) 0.49%.
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