The Data interpretation section is the most feared part of any exam for all candidates. The article attempts to break the section into components that can be easily understood weighed according to one's strengths and weaknesses, ultimately helping in fighting over the uncertainty and going to the exam with a pre-determined strategy to maximize the cutoff expected.
The data presentation in the questions across competitive exams is of various formats. While solving any data interpretation problem, proper time needs to be spent on the data given. With regard to tabular data, for example, we must clearly understand the expectations, the way to analyze data and also be able to anticipate the kind of questions that could be asked for such data.
As one glances through the tabular format for example, the eyes should look for the missing details to get a lead to begin with. The missing links also help us determine the probability of questions sought to be asked. Sticking to the same format again, it is obvious to expect a lot of calculations such as addition, multiplication, averages, percentages and rate of change. There could be a possibility of having a mix of easy and difficult questions. The easy questions would be directly evident from the data representation. It could also be framed in a way to calculate a parameter that in turn involves multiple calculations.
The options given for various questions can also be close enough to the answer which might make determining a choice tricky or confusing. But an important differentiator that leads you to a successful attempt of the section is understanding the data format right and expecting the right kind of questions from it. One must also understand that the DI section extends way into a candidate’s world beyond education lasting his entire corporate career. Apart from the tabular format, data is also of other types such as Bar diagrams, Line and pie charts, miscellaneous graphs, combinations and logic based sets. The bar diagrams pose comparison and calculative oriented questions while the line ones pose more questions of a comparison nature among metrics. The bar diagrams can be by way of vertical bars or stacked ones. The line diagrams also require conclusions to be determined looking at a slope.
On the contrary, Pie charts are more logically-inferenced and predominantly based on percentages. They may range from the easiest to the most complicated ones. The combination graphs may be a combination of line, pie and bar diagrams posed more of a logical nature and less calculation intensive. The miscellaneous ones may not be structured as the graphs may contain data represented by points or can also be radar graphs which might be for the mix of candidates considered above average. These graphs make the Data interpretation section time-consuming.
In the case of a logic based set, a student might require a combination of applying logic and arriving at a conclusion. The most interesting and risky part of the DI section, they may be in the form of puzzles which may sum to up to be a major proportion of the section.With this summarized overview, the candidates are expected to understand the structure of the data interpretation section, weigh them in accordance with their capabilities and come up with a strategy to attempt them with an aim to maximize their cutoff in this section. Most of the examinees for competitive exams like XAT and NMAT, who are anxious about this section need to ward off that thought and think of ways to ace data interpretation. All the best!
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