{"id":30891,"date":"2020-01-13T09:35:32","date_gmt":"2020-01-13T14:35:32","guid":{"rendered":"http:\/\/www.kaptest.com\/blog\/prep\/?p=30891"},"modified":"2020-09-11T20:40:11","modified_gmt":"2020-09-11T20:40:11","slug":"oat-quantitative-reasoning-data-sufficiency","status":"publish","type":"post","link":"https:\/\/wpapp.kaptest.com\/study\/oat\/oat-quantitative-reasoning-data-sufficiency\/","title":{"rendered":"OAT Quantitative Reasoning: Data Sufficiency"},"content":{"rendered":"

Data Sufficiency questions are quite different from the other questions you\u2019ll see on the Quantitative Reasoning test<\/a>.\u00a0The\u00a0example below\u00a0shows\u00a0the standard structure of this question type.
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\nNotice that the question stem only asks if the product of x, y, and z is equal to 1. It does not ask you to solve for the values of the given variables. The question also provides two pieces of information in two separate statements. No other information is given. This is a key feature of Data Sufficiency questions: you must use the statements, not just the question stem, to determine whether the data in the statements are enough (sufficient) to answer the question.
\nAnother distinct feature of Data Sufficiency questions is the format of the answer choices. Like we saw in Quantitative Comparison questions, all of the answer choices will be exactly the same in every question. In this case, each answer choice focuses on the \u201csufficiency\u201d or \u201cinsufficiency\u201d of the statements. In other words, does one, both, or neither of the statements provide enough information to answer the question? Since these answer choices will never change, the Kaplan Method includes an easy way to analyze the answer choices for strategic elimination.
\nAlthough these questions may seem strange at first, once you are familiar with their structure and associated tasks, they can be straightforward questions. Data Sufficiency questions are only asking you to assess whether or not you have enough information to answer the question; you don\u2019t need to solve for specific values. As such, many Data Sufficiency questions can be solved without any arithmetic. Instead, you can rely solely on critical thinking, as these questions are focused on testing your ability to assess presented data and make deductions from that information.
\nWhile data sufficiency questions appear to test you on basic arithmetic concepts like multiplication, addition, and inequalities, they often require your knowledge of less explicitly mentioned topics, such as number properties. For example, in the example above, it is easy to assume that x, y, and z are integers. However, the question does not provide any information to prove this assumption. Never assume that variables are integers or even positive numbers unless explicitly stated.
\n[\u00a0RELATED:\u00a0<\/strong>What’s a good OAT score?<\/a> ]
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THE BASIC PRINCIPLES OF DATA SUFFICIENCY<\/h3>
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\nEspecially because this question type is more abstract than Problem Solving, it\u2019s essential to have a strategic approach to every OAT Data Sufficiency question. Don\u2019t waste time or mental energy doing unnecessary calculations. A systematic approach will ensure that you find the most efficient solution to the problem and that you make as few careless and avoidable errors as possible. Here are some ways you can optimize your Data Sufficiency performance.
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Know How to Eliminate Data Sufficiency Answer Choices<\/em><\/h4>
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If Statement (1) is sufficient, the answer could only be (A) or (D). Eliminate (B), (C), and (E).
\nIf Statement (1) is insufficient, the answer could only be (B), (C), or (E). Eliminate (A) and (D).
\nIf Statement (2) is sufficient, the answer could only be (B) or (D). Eliminate (A), (C), and (E).
\nIf Statement (2) is insufficient, the answer could only be (A), (C), or (E). Eliminate (B) and (D).<\/p>\n

Using the mnemonic device 12TEN will help you keep track of these answer choices, allowing you to attack the question more efficiently and avoid considering an answer choice you\u2019ve already ruled out.
\nYou also want to avoid a common mistake on Data Sufficiency: choosing (C) when the answer is actually (A), (B), or (D). Remember: if either statement by itself is sufficient, then of course the two statements together will also be sufficient, since the statements are always true and never contradict each other. But (C) can be correct only when each statement alone is insufficient and combining the statements is necessary to obtain sufficiency.
\nYou should consider the statements together only if each is insufficient on its own. When you evaluate the statements together, keep in mind that each statement is true.
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Know the Two Types of Data Sufficiency Questions<\/em><\/h4>
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\nThere are two broad types of Data Sufficiency questions, and they play by slightly different rules. The two types are Value questions and Yes\/No questions. First, you need to determine which type of question you\u2019re dealing with, since this will determine your approach.
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