If a set of observations is normally distributed, then the percentage of observations differs from mean by more than $$ 1.3 \sigma $$ is: $$ \begin{array}{ll} ext { (a) } 19.36 \% & ext { (b) } 90.32 \% \ ext { (c) } 9.68 \% & ext { (d) None of these }\end{array} $$

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If a set of observations is normally distributed, then the percentage of observations differs from mean by more than $$ 1.3 \sigma $$ is: $$ \begin{array}{ll}	ext { (a) } 19.36 \% & 	ext { (b) } 90.32 \% \ 	ext { (c) } 9.68 \% & 	ext { (d) None of these }\end{array} $$

Dunn Morrison · Accepted Answer

The percentage of observations differing from the mean by more than $$1.3 \sigma$$ is **19.36%**.

If a set of observations is normally distributed, then the percentage of observations differs from mean by more than \( 1.3 \sigma \) is: \( \begin{array}{ll}\text { (a) } 19.36 \% & \text { (b) } 90.32 \% \\ \text { (c) } 9.68 \% & \text { (d) None of these }\end{array} \)

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If a set of observations is normally distributed, then the percentage of observations differs from mean by more than \( 1.3 \sigma \) is: \( \begin{array}{ll}\text { (a) } 19.36 \% & \text { (b) } 90.32 \% \\ \text { (c) } 9.68 \% & \text { (d) None of these }\end{array} \)

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