MHT CET · Maths · Statistics

If both mean and variance of 50 observations \(x_1, x_2, \ldots \ldots, x_{50}\) are equal to 16 and 256 respectively, then mean of \(\left(x_1-5\right)^2,\left(x_2-5\right)^2, \ldots \ldots\left(x_{50}-5\right)^2\) is

A \(357\)
B \(387\)
C \(377\)
D \(397\)

Verified Solution

Answer & Solution

Correct Answer

(C) \(377\)

Step-by-step Solution

Detailed explanation

Given that \(\mathrm{n}=50, \bar{x}=16\) and \(\sigma_x{ }^2=256\)
\(\therefore \sigma_x^2=\frac{1}{\mathrm{n}}\left(\sum_{i=1}^{50} x_i^2\right)-(\bar{x})^2 \)
\( \therefore 256=\frac{1}{50}\left(\sum_{i=1}^{50} x_i^2\right)-256 \)
\( \therefore \frac{1}{50}\left(\sum_{i=1}^{50} x_i^2\right)=512 \)
\( \therefore \sum_{i=1}^{50} x_i^2=25600\)
Now \(\sum_{i=1}^5\left(x_i-5\right)^2 =\sum_{i=1}^{50} x_i^2+25 \times 50-10 \sum_{i=1}^5 x_i \)
\( =25600+1250-8000\)
... [From (i) and (ii)]
\(\leq 18850\)
\(\therefore\) Required Mean \(=\frac{\sum_{i=1}^{50}\left(x_i-5\right)^2}{50}=\frac{18850}{50}=377\)

Apply the relevant identity from the chapter and substitute the values established in the previous step, keeping the original constraint in view.

Use the simplified expression to isolate the unknown, then plug the result back into the question setup to confirm the working is internally consistent.

Cross-check against a boundary or limiting case. Both the dimensional balance and the qualitative behaviour at the extreme should agree with the candidate answer.

Combine the steps above to identify the correct option. The remaining choices each fail at least one of the consistency, dimensional, or boundary checks.

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