Let X1, X2, ..,X, be a random sample from a Normal distribution with mean µ and variance o2. Consider the random variable, X.Which of the following properties are true? Select all that apply. On average, the sample mean is equal to the population mean. For any n, the sample mean is approximately normally distributed. The variance of the sample mean is equal to the population variance divided by n. For n sufficiently large, the sample mean is approximately normally distributed. For n sufficiently large, the distribution of the sample mean depends on the distribution of the population mean. For any n, the sample mean is exactly normally distributed. For n sufficiently large, the sample mean is exactly normally distributed. For any n, the distribution of the sample mean depends on the distribution of the population mean. 0000 00

MATLAB: An Introduction with Applications
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Let X1, X2, .., Xn be a random sample from a Normal distribution with mean u and variance o2. Consider the random variable, X.Which of the
....
following properties are true? Select all that apply.
On average, the sample mean is equal to the population mean.
For any n, the sample mean is approximately normally distributed.
The variance of the sample mean is equal to the population variance divided by n.
For n sufficiently large, the sample mean is approximately normally distributed.
For n sufficiently large, the distribution of the sample mean depends on the distribution of the population mean.
For any n, the sample mean is exactly normally distributed.
For n sufficiently large, the sample mean is exactly normally distributed.
For any n, the distribution of the sample mean depends on the distribution of the population mean.
Transcribed Image Text:Let X1, X2, .., Xn be a random sample from a Normal distribution with mean u and variance o2. Consider the random variable, X.Which of the .... following properties are true? Select all that apply. On average, the sample mean is equal to the population mean. For any n, the sample mean is approximately normally distributed. The variance of the sample mean is equal to the population variance divided by n. For n sufficiently large, the sample mean is approximately normally distributed. For n sufficiently large, the distribution of the sample mean depends on the distribution of the population mean. For any n, the sample mean is exactly normally distributed. For n sufficiently large, the sample mean is exactly normally distributed. For any n, the distribution of the sample mean depends on the distribution of the population mean.
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