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Bunuel
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Active GMAT Club Expert! Tag them with @ followed by their username for a faster response.
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The answer is B because if a set of terms have a SD and we want to add a new term in order to minimize the SD of that set then the new term must be closest to it's mean and closest to mean is mean itself. And if we want to increase it's SD then the term(s) must be farthest from it's mean.

Since, the two weights added are both equidistant i.e farther from it's mean weight, therefore, the SD will increase.
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Can you please explain this problem ?

plus, let say SD in this problem is 4 then the new SD of the boxes still increase or remain the same ?
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gmatophobia

AnujL
gmatophobia
Can you please explain this problem ?

plus, let say SD in this problem is 4 then the new SD of the boxes still increase or remain the same ?
AnujL Standard deviation denotes how dispersed the data set is with respect to the mean.

In this question, we know that the mean weight of all the boxes is 22 pounds. The heavier box is 26 pounds (4 pounds above the mean) and the lighter box is 18 pounds (4 pounds below the mean). Hence after the two boxes that were added, the mean does not change and the mean of all the boxes is still 22 pounds.

Consider this - You've $22 with you, one friend gives you $4 and you lend $4 to another friend of yours. After both transactions, you will still have $22 with you.

Now back to the question - So after the two boxes are added the mean is still 22 pounds, however, we have added two data points which lie at some distance away from the mean. Hence the data set is now more dispersed and the SD increases.

Note:
1) The original value of standard deviation is not of any relevance to this question. So whether you take the original SD as 3, 4, or 2, the analysis and the behavior that the standard deviation increases remain the same.
2) We were able to arrive at the conclusion only because the value of the mean didn't change.
­
I agree with the explanation and the approach taken to arrive at the correct answer. But I disagree with the 1st note which mentions that answer (that SD increases) is irrespective of the value of the original SD. Following is my reasoning:

If original SD is 3 then by a typical SD calculation formula, lets say sqrt (X/Y) = 3. Y is number of boxes (originally) and X is the numerator for a typical SD equation calculation.

Now 2 boxes of 18 and 26 pounds are added. So re-writing the SD equation

SD (revised) = SQRT [(X+ (18-22)^2 + (26-22)^2) / (Y+2)]
= SQRT [(X+32)/(Y+2)]

Now, lets try to prove that SD (revised) > SD (original), which means
=> [(X+32) / (Y+2)] > X/Y
=> X*Y + 32Y > X*Y + 2X
=> 16Y > X
=> X/Y <16
=> SD (original) < 4

This tells us that SD (revised) > SD (original) only when SD (original) <4. Thus, the answer depends on the SD(original) value and is not independent.­
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mean +/- 1 * SD covers 66.7% of the data of a sample space ( 22 + 3 = 25 and 22-3 = 19)

Now if you add 2 observations (18,26) which lie outside this area ( 19 to 25 ), then the deviation from mean is bound to increase.
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