Answer:
e) The mean of the sampling distribution of sample mean is always the same as that of X, the distribution from which the sample is taken.
Step-by-step explanation:
The central limit theorem states that
"Given a population with a finite mean μ and a finite non-zero variance σ2, the sampling distribution of the mean approaches a normal distribution with a mean of μ and a variance of σ2/N as N, the sample size, increases."
This means that as the sample size increases, the sample mean of the sampling distribution of means approaches the population mean. This does not state that the sample mean will always be the same as the population mean.
Answer:
7
Step-by-step explanation:
10+7+1+6+7+9+8+10+2+5
-----------------------------------
10
65 ÷ 10
= 6.5, round up, = 7
Answer:
oh 21
Step-by-step explanation:
1 times 12 is 12 and 3/4 times 12 is 36/4 =9. 9 plus 12 is 21
