1. The sampling distribution of sample means consists of ___________

(A) all the scores contained in a sample

(B) all the scores contained in the population

(C) the sample means for all the possible samples

(D) the mean computed for a specific sample of scores

2. The standard deviation in the sampling distribution of sample means is usually called __________

Group of answer choices

(A) the sampling error of mean

(B) the standard error of mean

(C) the sample mean

(D) the central limit mean

3.To obtain the sampling distribution of sample means, we need to __________________________.

Group of answer choices

(A) obtain data from a normal distribution in the population

(B) draw a sample, calculate its mean and standard error

(C) draw many samples, calculate the mean of each sample, and make a histogram of the means

(D) draw a sample with numerous data points

4. The population has 50,000 athletes. We randomly put these athletes on buses, and each bus has 50 people. So there are 1,000 buses. Within each bus, we calculate the average height of the 50 athletes in that particular bus. In the sampling distribution of average heights, each data point is based on ________ athletes.

5. The population has 20,000 athletes. We randomly put these athletes on buses, and each bus has 50 people. Within each bus, we calculate the average height of the 50 athletes in that particular bus. Because there are 400 buses, we have 400 average heights. Based on these 400 average heights, we have _______ sampling distribution(s) of average heights.

6.The population has 50,000 athletes. We randomly pick a sample of 2,000 athletes from the population, and calculate their average height. Based on the average height of these 2,000 people, we have _______ sampling distribution(s) of average heights.

7. To obtain the sampling distribution of sample means, we need to ___________

Group of answer choices

(A) use a large sample size

(B) have a large population

(C) draw numerous samples

(D) draw a large sample and then calculate the sample mean

(E) all of the above

8. Consider the following process. What will we get at the end of this process?

Step 1: draw a sample

Step 2: calculate the variance of this sample

Step 3: repeat Steps 1 & 2 numerous times

Step 4: make a histogram for all the sample variance values we have

Group of answer choices

(A) sample variance

(B) sample distribution of sample variance

(C) sampling distribution of sample variance

(D) sampling distribution of sample means

(E) standard error of sample means

9. Consider the following process. What will we get at the end of this process?

Step 1: draw a sample

Step 2: calculate the standard deviation of this sample

Step 3: repeat Steps 1 & 2 numerous times

Step 4: make a histogram for all the sample standard deviation values we have

Group of answer choices

(A) sample standard deviation

(B) standard error

(C) standard error of sampling distribution

(D) sampling distribution of standard errors

(E) sampling distribution of sample standard deviations

10. Consider the following process. What will we get at the end of this process?

Step 1: draw a sample

Step 2: calculate the mode of this sample

Step 3: repeat Steps 1 & 2 numerous times

Step 4: make a histogram for all the sample mode values we have

Group of answer choices

(A) sampling distribution of sample modes

(B) sampling distribution of sample means

(C) mode of sample distribution

(D) mode of population distribution

(E) mode of sampling distribution

Questions 11-13are based on the following scenario.

Suppose cans of cola are filled so that the actual amounts are normally distributed with a mean of 12.00 oz and a standard deviation of 0.11 oz. We useXto denote the weight of a can of cola; that is, X ~ N(12, 0.11)

11. If we randomly pick a can of cola from the production line, there is _________% probability that the can of cola we get is heavier than 12.05 oz.

12. A supermarket sells this type of cola in boxes, and each box has 36 cans. We consider each box as a random sample of size n = 36. If we randomly pick a box from the supermarket, there is ________% probability that the average weight of the box of 36 cans exceeds 12.05 oz.

13. Which case is more likely to appear?

(I) a can of cola weights above 12.05 oz

(II) the average weight of 36 cans of cola is above 12.05 oz

Group of answer choices

(a) Case (I) is more likely to appear

(b) Case (II) is more likely to appear

(c) It depends on the standard error

(d) (I) and (II) are about equally likely

Questions 14-17 are based on the following scenario.

Suppose the distribution of family incomes of all the US households ispositively skewedwith mean 71,000 and standard deviation 15,000.

14. If I randomly pick a family in the US, what is the probability that this family's income is below 70,000?

Group of answer choices

(a) 7%

(b) 47.21%

(c) 2.79%

(d) there is not enough information

15. I randomly pick 2000 families in the US and make a histogram of the incomes of these 2000 families. What would the histogram look like?

Group of answer choices

(a) positively skewed

(b) negatively skewed

(c) normal

(d) approximately normal

16. If I drawnumeroussamples from the US and each sample has 2000 families. For each sample I calculate theaverage incomeof the families in that particular sample. What would the sampling distribution ofaverage family incomeslook like?

Group of answer choices

(a) positively skewed

(b) negatively skewed

(c) normal

(d) approximately normal

17. We randomly select 2000 families. There is __________% probability that the average income of this group of 2000 families is below 70,000.