MHT CET · Maths · Statistics
If variance of \(x_1, x_2 \ldots \ldots, x_{\mathrm{n}}\) is \(\sigma_x^2\), then the variance of \(\lambda x_1, \lambda x_2, \ldots \ldots, \lambda x_n(\lambda \neq 0)\) is
- A \(\lambda \cdot \sigma_x\)
- B \(\lambda \cdot \sigma_x^2\)
- C \(\lambda^2 \cdot \sigma_x\)
- D \(\lambda^2 \cdot \sigma_x^2\)
Answer & Solution
Correct Answer
(D) \(\lambda^2 \cdot \sigma_x^2\)
Step-by-step Solution
Detailed explanation
When each item of a data is multiplied by \(\lambda\), variance is multiplied by \(\lambda^2\).
\(\therefore \quad\) New variance \(=\lambda^2 \cdot \sigma_x^2\)
\(\therefore \quad\) New variance \(=\lambda^2 \cdot \sigma_x^2\)
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