# GMAT Tip of the Week: Raising Your Data Sufficiency Accuracy From 33% To 99%

You’re looking at a Data Sufficiency problem and you’re feeling the pressure. You’re midway through the GMAT Quantitative section and your mind is spinning from the array of concepts and questions that have been thrown at you. You know you nailed that tricky probability question a few problems earlier and you hope you got that last crazy geometry question right. When you look at Statement 1 your mind draws a blank: whether it’s too many variables or too many numbers or too tricky a concept, you just can’t process it. So you look at Statement 2 and feel relief. It’s nowhere near sufficient, as just about anyone even considering graduate school would know immediately. So you smile as you cross off choices A and D on your noteboard, saying to yourself: “Good, at least I have a 33% chance now.”

You’re better than that.

Too often on Data Sufficiency problems, people are impressed by giving themselves a 33% or even 50% chance of success. Keep in mind that guessing one of three remaining choices means you’re probably going to get that problem wrong! And of more strategic importance is this: if one statement is dead obvious, you haven’t just raised your probability of guessing correctly – you should have just learned what the question is all about!

If a Data Sufficiency statement is clearly insufficient, it’s arguably the most important part of the problem.

Consider this example:

What is the value of integer z?

(1) z represents the remainder when positive integer x is divided by positive integer (x – 1)

(2) x is not a prime number

Many examinees will be thrilled here to see that statement 2 is nowhere near sufficient, therefore meaning that the answer must be A, C, or E – a 33% chance of success! But a more astute test-taker will look closer at statement 2 and think “this problem is likely going to come down to whether it matters that x is prime or not” and then use that information to hold Statement 2 up to that light.

For statement 1, many will test x = 5 and (x – 1) = 4 or x = 10 and (x – 1) = 9 and other combinations of that ilk, and see that the result is usually (always?) 1 remainder 1. But a more astute test-taker will see that word “prime” and ask themselves why a prime would matter. And in listing a few interesting primes, they’ll undoubtedly check 2 and realize that if x = 2 and (x – 1) = 1, the result is 1 with a remainder of 0 – a different answer than the 1, remainder 1 that usually results from testing values for x. So in this case statement 2 DOES matter, and the answer has to be C.

Try this other example:

What is the value of x?

(1) x(x + 1) = 2450

(2) x is odd

Again, someone can easily skip ahead to statement 2 and be thrilled that they’re down to three options, but it pays to take that statement and file it as a consideration for later: when I get my answer for statement 1, is there a reason that even vs. odd would matter? If I get an odd solution, is there a possible even one?

Factoring 2450 leaves you with consecutive integers 49 and 50, so x could be 49 and therefore odd. But is there any possible even value for x, a number exactly one smaller than (x + 1) where the product of the two is still 2450? There is: -50 and -49 give you the same product, and in that case x is even. So statement 2 again is critical to get the answer C.

And the lesson? A ridiculously easy statement typically holds much more value than “oh this is easy to eliminate.” So when you can quickly and effortlessly make your decision on a Data Sufficiency statement, don’t be too happy to take your slightly-increased odds of a correct answer and move on. Use that statement to give you insight into how to attack the other statement, and take your probability of a correct answer all the way up to “certain.”

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By Brian Galvin