Answer:
Se=1.2
Step-by-step explanation:
The standard error is the standard deviation of a sample population. "It measures the accuracy with which a sample represents a population".
The central limit theorem (CLT) states "that the distribution of sample means approximates a normal distribution, as the sample size becomes larger, assuming that all samples are identical in size, and regardless of the population distribution shape"
The sample mean is defined as:
And the distribution for the sample mean is given by:
Let X denotes the random variable that measures the particular characteristic of interest. Let, X1, X2, …, Xn be the values of the random variable for the n units of the sample.
As the sample size is large,(>30) it can be assumed that the distribution is normal. The standard error of the sample mean X bar is given by:
If we replace the values given we have:
So then the distribution for the sample mean is:
