If random samples of size n are drawn from a large population (N > 20n) with a mean u and standard deviation o, then the sampling distribution of the sample means has a standard deviation (also called standard error) oz of. On

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If random samples of size \( n \) are drawn from a large population (\( N > 20n \)) with a mean \( \mu \) and standard deviation \( \sigma \), then the sampling distribution of the sample means has a standard deviation (also called standard error) \( \sigma_{\bar{x}} \) of...

- \( n \)
- \( \mu \)
- \( \frac{\mu}{\sqrt{n}} \)
- \( \frac{\mu}{n} \)
- \( \sigma \)
- \( \frac{\sigma}{\sqrt{n}} \)
- \( \frac{\sigma}{n} \)
Transcribed Image Text:If random samples of size \( n \) are drawn from a large population (\( N > 20n \)) with a mean \( \mu \) and standard deviation \( \sigma \), then the sampling distribution of the sample means has a standard deviation (also called standard error) \( \sigma_{\bar{x}} \) of... - \( n \) - \( \mu \) - \( \frac{\mu}{\sqrt{n}} \) - \( \frac{\mu}{n} \) - \( \sigma \) - \( \frac{\sigma}{\sqrt{n}} \) - \( \frac{\sigma}{n} \)
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