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# GMAT Tips – GMAT Data Sufficiency: The lazy person’s favorite question type?

Today’s GMAT Tip comes to us from Kaplan. In this article, Kaplan GMAT guest author Kurt Keefner provides helpful tips for answering Data Sufficiency questions on the quantitative section of the GMAT:

About 100 years ago Frank B. Gilbreth  was famous for pioneering a field he called “motion study.”  He specialized in making factories more efficient.  When Gilbreth first walked into a factory he was helping, what he did was to ask to meet the laziest worker there, because he figured that that person had already figured out how to be efficient.

We can all take a cue from Mr. Gilbreth when it comes to the GMAT.  A general principle is:  Do no more work than is necessary to get the answer.  Nowhere does this principle apply more than on that unique question type known as Data Sufficiency.

Data Sufficiency is like a Zen puzzle:  the answer to the question is not the answer to the problem.  The answer to the problem is what combination of data statements would be sufficient to answer the question.  You may or may not need to answer the question in order to answer the problem.  If you answer the question when you don’t need to, you are failing to apply our principle from above—only do the minimum amount of work required.

Let’s try an example from the Kaplan course to make this point more concrete:

Hallie has only nickels, dimes and quarters in her pocket.  If she has at least 1 of each kind of coin and has a total of \$2.75 in change, how many nickels does she have?

(1)  She has a total of 21 coins, with twice as many dimes as nickels.

(2)  She has \$1.50 in quarters.

Now this question is certainly answerable.  You might have to play with the information, do a little substitution, a little combination, but eventually you’d figure out that she had 5 nickels. Now what do you do with that number?  There is no answer choice for 5.  There is no way to enter your discovery at all.  Strictly speaking the information is useless.

Furthermore, if you focused on answering the question about Hallie’s nickels instead of the data sufficiency question that is being asked, chances are that you would use all the information given in both statements instead of considering them separately.  (The problem is easier to solve if you do.)  In that case, you will perhaps conclude that the statements taken together are sufficient to answer the question, when in fact, statement 1 by itself is sufficient.

Lastly, this whole process of solving for the number of nickels takes a lot of time– time you probably wish you could use on other problems.

So how would a “lazy person” approach this question?  The lazy person would never just dive in and start sifting information, but would take a bird’s-eye view.  He or she would look for the concept.  Data Sufficiency is concept math.

Our lazy student would look at the question stem and see that there are three unknowns (nickels, dimes and quarters), that they total up to a definite amount and that he is being asked for the value of one of them separately.  That would strongly suggest a system of equations.

Next our lazy student would recall the rule for systems of equations, which is that you must have as many distinct equations as you have variables in order to solve for the individual variables.  How many equations does the stem give us?  One, for the total dollars.  So we need two more.

Statement 1 gives us two more.  That there are 21 coins would give us one equation, and that there are twice as many dimes as nickels would give us the other.  (Note, an equation to be useful does not have to have all the variables in it, so the lack of quarters in the second equation doesn’t matter.)  Together with the stem, that makes three equations, which allow us to solve the system (which we needn’t bother to do).

Statement 2 only gives us one more equation, so it is not sufficient, and the answer is Statement 1 alone is sufficient.

Notice that our lazy student did not even bother to translate the words into formal equations.  It’s enough to know that you COULD do so.

So if you find yourself tempted to do extensive mathematical calculations on a GMAT Data Sufficiency problem—remember the “lazy student”, and that the secret on Data Sufficiency problems is that the answer to the mathematical question doesn’t matter in most instances.  Keep your eye on the concept being tested rather than the details of the execution.

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