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Next Generation GMAT: Table Analysis

Launching in June 2012, the Next Generation GMAT exam will include a 30-minute Integrated Reasoning section with four new question formats, which measure skills that management professors have identified as important for incoming students to have. This is the third in a series of Graduate Management News articles spotlighting the new question formats, following articles on Multi-Source Reasoning and Graphics Interpretation.

Skills tested: Table Analysis questions measure a test taker’s ability to analyze data tables to find patterns and draw conclusions and to organize information to solve problems efficiently. Sortable tables typically include columns of numbers, and Table Analysis questions often measure quantitative analytical skills. However, some columns may be sorted alphabetically, and some questions will assess skills that are not strictly mathematical—for example, identifying relationships within data, identifying which data satisfy certain conditions, or determining whether data are consistent with a given hypothesis or principle.

Click on the detail for an interactive sample question in Adobe Flash

Description: Each Table Analysis question includes a sortable table of information and several answer statements. The table must be analyzed to help determine whether each of the answer statements meets one of two conditions (e.g., true/false, yes/no, inferable/not inferable). The question may also include brief text with the data table. Test takers are able to sort the table by columns, similar to sorting a spreadsheet, to put the elements in each column in numeric or alphabetical order. While test takers are able to change answers within the question before moving on to the next question, they must respond to all of the answer statements before moving on.

Relevance: There is more data available now than ever before. Computerized spreadsheets have made it possible to analyze large quantities of data quickly, so knowing how to best organize data to find patterns and extract meaningful information has become more important. Business schools build on students’ ability to organize data to extract meaning by teaching them to use data to drive decision-making.

Quote: “Analytical approaches to business problems─often required in finance, operations management, and other specialties─require facility with determining patterns in data.  With the table analysis question, we are able to see if a student is able to extract simple patterns through sorting, determining extreme values, and counting.  If we know that students are able to quickly and easily analyze data at this level, we are then able to take them, through the MBA curriculum, into more advanced business analytics.  Without that baseline, however, students struggle with the material required for an MBA.”

─Michael Trick
Professor of Operations Research
Associate Dean, Research
Tepper School of Business
Carnegie Mellon University

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