1. Which of the following is correct about the sampling distribution of the sample mean using the Central Limit Theorem?
A. The mean of the sampling distribution of the means is not equal to the mean of the
population
B. As the sample size n increases, the sampling distribution of the means approaches a normal
distribution
C. The variance of the sampling distribution of the means is equal to the variance of the
population multiplied by the sample size n
D. The standard deviation of the sampling distribution of the means is equal to the standard
deviation of the population multiplied by the square root of the sample size n.
2. Which of the following refers to the standard deviation of a sampling distribution?
A. It is the sum of squares.
B. It is the standard tror of the nitai.
C. It only applies only to population data.
D. It can be larger than the standard deviation for the population.
3. Who is the French-born Mathematician who proved the first version of the Central
Limit Theorem?
A. Abraham de Moivre
B. Aristotle
C. Aleksander Lyapunov​