Suppose a simple random sample of size n is drawn from a large population with mean muμ and standard deviation sigmaσ. the sampling distribution of x overbarx has mean mu subscript x overbarμxequals= and standard deviation sigma subscript x overbarσxequals=

a.) The Mean mu Subscript x overbarμxequals= μ

b.) The standard deviation sigma Subscript x overbarσxequals= σ overbar square root of n.

Therefore the sample mean is equal to the population mean, but the standard error of the mean on the other hand depends on the sample size.

We notice also, that as n increases, sigma x over barσx reduces. Therefore n is inversely proportional to sigma x barσx.

i feel as if they would both catch on before to long because they would see them to frequent