Sampling distribution of mean is very close to the standard normal distribution when
A. Population is normally distributed
B. Population is not normally distributed, but sample size is large
C. Both A and B
D. Neither A nor B
Answer: Option A
A. Population is normally distributed
B. Population is not normally distributed, but sample size is large
C. Both A and B
D. Neither A nor B
Answer: Option A
A. The central limit theorem
B. The law of statistical regularly
C. The law of inertia of large numbers
D. None of the above
The difference between sample statistic and its corresponding population parameter is
A. Sampling error
B. Measurement error
C. Coverage error
D. Non-response error
A. Both (A) and (R) are true
B. (A) is true, but (R) is false
C. (A) is false, but (R) is true
D. Both (A) and (R) are false
Join The Discussion