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Stats: Modeling the World - Bock, Velleman, & DeVeaux
Chapter 18: Sampling Distribution Models
Key Vocabulary:
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sampling distribution model
sampling error
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sampling variability
sampling distribution model
for a proportion
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Central Limit Theorem
sampling distribution model
for a mean
Calculator Skills:
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normalcdf(
1.
What is meant by the sampling distribution model of a sample proportion?
2.
What is meant by sampling variability?
3.
What is the difference between p and pö ?
4.
What is the “catch” when using the normal model to approximate the distribution of sample
proportions?
5.
Describe the conditions for using the Normal model for the distribution of sample
proportions.
6.
What is the sampling distribution model for a proportion?
Chapter 18: Sampling Distribution Models
Stats: Modeling the World - Bock, Velleman, & DeVeaux
7.
Why are sampling distribution models so important to Statistics?
8.
State the Central Limit Theorem (CLT).
9.
State the assumptions and conditions associated with the CLT.
10. What is the sampling distribution model for a mean?
11. _____ vary less than individual data values.
12. In order to decrease the standard deviation of the sampling distribution by half, what should
be done to the sample size?
13. The Central Limit Theorem doesn’t talk about the distribution of data from the sample. It
talks about the sample means and sample proportions of _____ _____ _____ _____ drawn
from the same population.
14. Explain the statement, “at the heart is the idea that the statistic itself is a random variable”.
Chapter 18: Sampling Distribution Models