Have an account?
Skip to Content
Build your own quiz
Suggestions for you
12 questions
Show Answers
See Preview
- 1. Multiple Choice
Suppose we have a population that is 49% male. If we take a random sample from that population and determine the percent of our sample that is male, we refer to this proportion as...
p
p-hat
the sample mean
the sampling distribution
- 2. Multiple Choice
When sampling from a population with proportion p, the distribution of sample proportions (p-hat) will vary. What will be the mean of all possible sample proportions?
p
- 3. Multiple Choice
When sampling from a population with proportion p, the sample outcomes will vary. Which of the following represents the sampling distribution?
p
- 4. Multiple Choice
If certain preconditions are met, we can assume the distribution of all possible p-hats (results of samples taken from the same population) will be normally distributed. Which of the following is NOT a precondition that needs to be met?
The sample is drawn randomly from the population
All participants are independent of each other (at least in regards to the characteristic in question)
- 5. Multiple Choice
Assume we are sampling to find the percent of people of Asian descent from a population that is actually 20% Asian (p=.2). Which of the following sample sizes would meet the minimum requirement for assuming the distribution of sampling proportions is normal? (Hint-remember your pre-conditions). Select ALL that would be considered big enough.
10
20
50
75
- 6. Multiple Choice
One of the often overlooked pre-conditions for sampling is the "10% rule." Your sample can't exceed 10% of the population, or else you significantly change the proportion of the population simply by removing your sample. Assume we are sampling from a population of 1700 (Warwick HS). Which of the following sample sizes would not violate the 10% rule? Choose all that qualify.
100
150
200
250
- 7. Multiple Choice
Given a population with proportion p=.35. Which of the following is true of a sample of size 50? Assume the sample is taken randomly and all individuals are independent of each other, and we have not violated the 10% rule.
Pre-conditions for normality have not been met (the sample is too small).
Sample is big enough, p= .50 and sampling distribution = .35
Sample is big enough, p= .35 and sampliing distribution = .067
Sample is big enough, p= .35 and the sampling distribution = .107
- 8. Multiple Choice
Assume we have met all the pre-conditions to ensure our distribution of all possible sample proportions is normal. If I'm drawing a sample of size 100 (n=100) from a population that is 49% men (so p=.49), what is the probability that my sample proportion p-hat will be less than .40? Remember this proportion is normally distributed.
P(p-hat<.40)=....036
.452
.490
.964
- 9. Multiple Choice
Given a box of 1000 marbles that is 28% red, if I randomly select 36 marbles, have I drawn a large enough sample to use the normal distribution?
No, because
Yes, because
no, becuase
- 10. Multiple Choice
Given the same box of marbles with 28% red, if I randomly select 36 marbles what is the probability that I will have at least 9 red marbles in my sample?
In this case p = 9/36 = .25
Hint: remember this is a "greater than or equal" problem
Sample isn't large enough to use the normal distribution
P(p-hat>.28) = .50
P(p-hat>.28) = .66
P(p-hat>.28) = .72
- 11. Multiple Choice
Newport News is 40% black. What is the probability that if we randomly selected 25 potential jury members for a trial, no more than 10 would be black?
µp̂=.4, σp̂=.25, P(p̂<10/25)=P(p̂<.4)=0.72
µp̂=.4, σp̂=.098, P(p̂<10/25)=P(p̂<.4)=0.50
µp̂=.4, σp̂=.098, P(p̂<10/25)=P(p̂<.4)=0.37
- 12. Multiple Choice
If a city population is 54% female and we randomly select 100 people to participate in a free Statistics class, what is the probability that we would have between 40 and 60 women in our sample?
Think carefully. What is p? What is n? What range of values of p̂ am I interested in? And finally, is the distribution normal (preconditions) and if so, what is the sampling error (distribution)? Don't forget to switch everything to proportions.
Our sample is too small to consider the distribution of p̂ normal.
P(.40≤ p̂ ≤.60) = .50
P(.40≤ p̂ ≤.60) = .762
P(.40≤ p̂ ≤.60) = .883
- Answer choicesTagsAnswer choicesTags