4 must follow steps to approach data sufficiency questionsSolving Data Sufficiency questions is a nightmare for a lot of candidates preparing for CAT. Here are 4 steps you must follow to get your data suffiency questions right… Data Sufficiency 4 must follow steps to approach are:
STEP 1: Identify the type
There are two basic types of data sufficiency questions in CAT:
1. Numerical value questions- These questions ask whether it is possible to arrive at an exact numerical solution given certain information like What is the value of x ? or What is John’s salary?
2. “Yes or no” questions- These questions require only a yes or no answer like Is x greater than 1? or Is John’s salary more than 10,000 per year?
STEP 2: Grab the stem
Pay careful attention to any information provided in the stem of the question. Consider these 2 questions for better understanding
Question 2- What is Paul’s annual income?
(1) Paul’s annual income is $20,000 less than Edna’s. (2) Edna’s annual income is 3 times Paul’s.
Question 1- Paul and Edna have a combined annual income of $40,000. What is Paul’s annual income?
(1) Paul’s annual income is $20,000 less than Edna’s. (2) Edna’s annual income is 3 times Paul’s.
Now, Both the questions have same statements and basic question i.e What is Paul’s annual income?, but what the stem says about it has a huge impact on the answer.
STEP 3: Isolation is the key
Consider each statement in isolation. Test each statement for sufficiency independently of the other statement.The trickiest call in data sufficiency is how the two statements work together—so do not go there until you have established that it is necessary to do so. First,determine whether statement (1) is sufficient. Second, determine whether statement(2) is sufficient.
STEP4 : Use Elimination method
Eliminate choices and, if necessary, guess. Even if you are unable to arrive at a complete solution to the problem, you can often eliminate two or three answer choices by carefully analyzing the question and statements.
Data Sufficiency 4 must follow steps to approach
4 must follow steps to approach data sufficiency questionsSolving Data Sufficiency questions is a nightmare for a lot of candidates preparing for CAT. Here are 4 steps you must follow to get your data suffiency questions right… Data Sufficiency 4 must follow steps to approach are:
STEP 1: Identify the type
There are two basic types of data sufficiency questions in CAT:
1. Numerical value questions- These questions ask whether it is possible to arrive at an exact numerical solution given certain information like What is the value of x ? or What is John’s salary?
2. “Yes or no” questions- These questions require only a yes or no answer like Is x greater than 1? or Is John’s salary more than 10,000 per year?
STEP 2: Grab the stem
Pay careful attention to any information provided in the stem of the question. Consider these 2 questions for better understanding
Question 2- What is Paul’s annual income?
(1) Paul’s annual income is $20,000 less than Edna’s. (2) Edna’s annual income is 3 times Paul’s.
Question 1- Paul and Edna have a combined annual income of $40,000. What is Paul’s annual income?
(1) Paul’s annual income is $20,000 less than Edna’s. (2) Edna’s annual income is 3 times Paul’s.
Now, Both the questions have same statements and basic question i.e What is Paul’s annual income?, but what the stem says about it has a huge impact on the answer.
STEP 3: Isolation is the key
Consider each statement in isolation. Test each statement for sufficiency independently of the other statement.The trickiest call in data sufficiency is how the two statements work together—so do not go there until you have established that it is necessary to do so. First,determine whether statement (1) is sufficient. Second, determine whether statement(2) is sufficient.
STEP4 : Use Elimination method
Eliminate choices and, if necessary, guess. Even if you are unable to arrive at a complete solution to the problem, you can often eliminate two or three answer choices by carefully analyzing the question and statements.Category :
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