One of the big reasons why the those who have good language skills do well on the GMAT is that even the Quantitative section has a lot of English comprehension. The Quantitative section of the GMAT has quite a few Word Problems or problems involving barely any symbols and lots of language in both the Problem Solving and the Data Sufficiency formats. This is especially challenging for non-native speakers of English who take the test since they tend to put English and Math or Verbal and Quantitative skills into separate compartments. Asian test-takers, especially those from India, are used to thinking of Math problems in terms of notational or algebraic language rather than English. So the skill to convert English into either Logic or Algebra is something that test-takers have to master if they aim to score a 50 or more on the Quant section. This post will deal the steps involved in mastering this skill and solving these seemingly lengthy problems faster.
The GMAT Quant generally throws up a few problems that designed to act as speed-breakers during the course of the 75-minute Quantitative section. Not surprisingly, these questions are what are usually referred to as the Roman Numeral problems — information followed by III statements, with the question asking you identify the statements that could be true, must be true or is true. Depending upon the the question stem — could be or must be — you need to follow a specific approach to nail these questions without wasting much time. But one still has to proceed with the knowledge that these problems will take a tad longer to solve than the others since the equivalent of since almost three questions is built into one question.
One of the reasons why the GMAT is my favourite test of all is that it is so well defined in terms of the skills tested and consistently so. One of the things that is absolutely essential to remember on the GMAT Problem Solving (PS) is that the test-setters do not want you to do donkey work with respect to calculation. The leading companies in the world are not paying thousands of dollars to hire graduates from premier b-schools to do what a calculator can do!
In one of the earliest Data Sufficiency posts on this blog, which you can read here and here, we discussed how the GMAT test-makers use the C-Trap to lure test-takers into making a mistake. The beauty of such questions is that the test-takers d not even realise that they have made a mistake. On the contrary they are very confident that they have answered it correctly. The C-Trap is set to lull test-takers into thinking that they can easily get the answer by using both the statements. But while both statements together will give you the answer, the question you need to ask is whether both statements are in fact required. Remember you need to choose option (C) only if both statements ARE required.
It goes without saying that the toughest GMAT Quant Problems are GMAT Data Sufficiency questions involving Inequalities. One specific issue that arises when solving tougher questions of this type is how to combine the two statements when both involve inequalities. Let us use two GMAT Data Sufficiency questions to understand how to go about combining inequalities.
Sometimes the process of teaching helps the teacher as much as the student. I was in Hyderabad the last weekend, conducting a GMAT Boot Camp for IMS Hyderabad students and during the course of the session, I discovered a better way to solve an old problem. Towards the end of a long and grueling day of solving 700-800 level problems we came to this Data Sufficiency problem as part of the segment where we focus specifically on the toughest type of Data Sufficiency problems – those involving inequalities.
In the previous Quantitative post , we saw how seemingly tough and time-consuming Data Sufficiency problems usually require a certain amount of pre-work. In most cases if the pre-work is done properly, you will precisely know what information is required to answer the question even before you go to the statements. The GMAT question below is another one of such problems.
The toughest GMAT Quant problems are usually Data Sufficiency questions involving numbers systems and inequalities. These problems tend to pose a lot of difficulties for test-takers because they seem to invite test-takers to plug in numbers and once they take that road, test-takers find themselves taking an inordinate amount of time. Once test-takers become aware of the of the ticking of the timer, panic sets in and even if they do manage to solve it, test-takers are still unsure of their answer. Answering these type of questions correctly is key to moving from a scaled score of 48 to a scaled score of 50 on the Quant.
One of the biggest challenges on the GMAT® is the battle against the timer. But the first thing that test-takers have to realize that it is not a test where a section cannot be completed in 75 minutes. Even the seemingly time-taking problems or calculations always have a straightforward solution provided you pause to think about the best way of going about solving a problem rather than jump into it. Usually the speed-breakers are Data Sufficiency questions involving inequalities. The first reaction of test-takers is to randomly plug numbers and see how things will pan out. Since they have not taken the time to first define the problem well, plugging numbers tends to become a trial and error process in the hope of hitting upon the answer rather than a process of testing the inequality! Over the next few Quantitative posts we will look at methods to effectively tackle Data Sufficiency problems involving inequalities. One of the first methods of decreasing the solving time required on these problems is to test the converse of the …
On the GMAT it is very likely that test-takers will encounter problems that involve pure approximation. The key to solving these problems is to be aware of two things: A. The answer need not be calculated precisely B. Eliminating incorrect answer options might be the best solution