Liberty University Online Academy

BMAL 590

Section 4: Sampling Distributions

1)The standard deviation of the sampling distribution of x? is also called the

central limit theorem.

2. The Central Limit Theorem states that, if a random sample of size n is drawn from a population, then the sampling distribution of the sample mean

3. If all possible samples of size n are drawn from a population, the probability distribution of the sample mean x? is called

4. Sampling distributions describe the distributions of

5. Suppose X has a distribution that is not normal. The Central Limit Theorem is important in this case because

6. As a general rule, the normal distribution is used to approximate the sampling distribution of the sample proportion only if

7. The standard deviation of p? is also called the_________________

8. If two populations are normally distributed, the sampling distribution of the difference in the sample means,_________________

9. if two random samples of sizes n₁ and n₂ are selected independently from two non- normally distributed populations, then the sampling distribution of the sample mean difference, x?₁ - x?₂

10. If all possible samples of size n are drawn from an infinite population with a mean of u and a standard deviation of o, then the standard error of the sample mean is inversely proportional to             .

11. In a given year, the average annual salary of a senior manager was $189,000 with a standard deviation of $20,500. If a sample of 50 senior managers was taken, then probability that the sample mean will be $192,000 or more is                                                                                                   .

12. If two random samples of sizes n1 and n2 are selected independently from two populations with means m1 and m2, then the means of x1 - x2 equals                                                                              . M1 + M2

13. The t-distribution approaches the normal distribution as the                                 . Degrees of freedom increases

14. The              can be the derivative of the sampling distribution.
15. The concept that allows us to draw conclusions about the population based strictly on sample data without having any knowledge about the distribution of the underlying population is

16. Each of the following are characteristics of the sampling distribution of the mean except

17. Suppose you are given 3 numbers that relate to the number of people in a university student sample. The three numbers are 10, 20, and 30. If the standard deviation is 10, the standard error equals