GRE Data Interpretation 101 | The Best Tips & Tricks
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6 سال پیش
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The purpose of Data Interpretation
The purpose of Data Interpretation questions is right there in the name. These questions require you, the test taker, to interpret data presented in various formats — specifically tables, graphs, and other visual presentations.
There are 3 Data Interpretation questions in each Quant section on the test. Since there are two scored Quant sections on any given exam, this gives 6 scored Data Interpretation questions on the exam. Out of 40 questions, that's not an insignificant number — about 15% of all Quant questions! This means that mastering our Data Interpretation strategy is critical to your GRE score.
All three questions in one section are presented together, as they all go with one set of data— this set of data may include multiple tables, graphs, diagrams, etc. We can think of these a lot like multi-question Reading Comprehension passages – a bunch of info given to us up top that is used to answer a series of questions. Now, like we are on Reading Comprehension, we're always going to be told which questions will be based on the data presented in the question.
The questions in Data Interpretation sets can come in multiple types — they can be multiple choice (select one), multiple choice (select one or more), or numeric entry. The one thing they cannot be is quantitative comparison.
Now, how can we approach these question sets for the highest likelihood of success?
There are 3 Data Interpretation questions in each Quant section on the test. Since there are two scored Quant sections on any given exam, this gives 6 scored Data Interpretation questions on the exam. Out of 40 questions, that's not an insignificant number — about 15% of all Quant questions! This means that mastering our Data Interpretation strategy is critical to your GRE score.
All three questions in one section are presented together, as they all go with one set of data— this set of data may include multiple tables, graphs, diagrams, etc. We can think of these a lot like multi-question Reading Comprehension passages – a bunch of info given to us up top that is used to answer a series of questions. Now, like we are on Reading Comprehension, we're always going to be told which questions will be based on the data presented in the question.
The questions in Data Interpretation sets can come in multiple types — they can be multiple choice (select one), multiple choice (select one or more), or numeric entry. The one thing they cannot be is quantitative comparison.
Now, how can we approach these question sets for the highest likelihood of success?
6 سال پیش
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