KI UNIQUE DI & DS SECTION

KI UNIQUE DI & DS SECTION

Data Sufficiency

DS can come under any section. But we have categorized it under Quantitative Section.

• The examinee basically has to decide whether or not he/she has enough information in hand to answer a given question.
• The examinee must be through with all the alternatives of data sufficiency so that he may decide quickly for the choice of the related alternative.
• Be careful not to carry over any information from one numbered statement to another. (Making this mistake is remarkably easy, especially under time pressure and in a momentary lapse of concentration.)
• If a question asks for a numerical value (as opposed to a quantitative expression that includes variables), the question is answerable only if a numbered statement (1 or 2) yields one and only one possible numerical answer--not a range of values.
• In distinct contrast to Problem Solving geometry figures, Data Sufficiency figures are not necessarily drawn proportionately--unless a figure indicates explicitly that it is drawn to scale. Do NOT rely on your eye to measure angle sizes, line segment length, or areas.

EXAMPLE OF DS

1. How long will it take for two pipes A and B to fill an empty cistern if they worked alternately for an hour each?
   A. Working alone, Pipe A can fill the cistern in 40 hours
   B. Pipe B is one third as efficient as Pipe A

Correct choice (3). Correct Answer - (Both the statements together are sufficient to answer the question.)

DATA INTERPRETATION (DI)

• It is quite evident that only calculation skills or analytical skill will not help the cause of solving Data Interpretation in MAT. You need to have both of these.
• Learning different types of graphs is never a problem. You can pick up any business daily or any business magazine where you can find graphs.
• One of the effective ways of learning DI is framing your own questions. By doing so, you are putting yourself in the examiner’s shoes and this will definitely open up your mind to new ideas.
• It is thus necessary to understand the characteristics of data interpretation so as to be able to deduce accurately from the given data.

EXAMPLE: Answer the question on the basis of the information given below.

The percentage of respondents aged less than 50 years is at least

• 40%
• 46.67%
• 33.33%
• 50%