7. The sampling distribution refers to: A. the distribution of the various sample sizes which might be used in a given study B. the distribution of the different possible values of the sample mean together with their respective probabilities of occurrence C. the distribution of the values of the items in the population D. the distribution of the values of the items actually selected in a given sample
7. The sampling distribution refers to: A. the distribution of the various sample sizes which might be used in a given study B. the distribution of the different possible values of the sample mean together with their respective probabilities of occurrence C. the distribution of the values of the items in the population D. the distribution of the values of the items actually selected in a given sample
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
Transcribed Image Text:7. The sampling distribution refers to:
A. the distribution of the various sample sizes which might be used in a given study
B. the distribution of the different possible values of the sample mean together with their respective
probabilities of occurrence
C. the distribution of the values of the items in the population
D. the distribution of the values of the items actually selected in a given sample
8. The Central Limit Theorem states that:
A. if n is large then the distribution of the sample can be approximated closely by a normal curve
B. if n is large, and if the population is normal, then the variance of the sample mean must be small
C. ifn is large then the sampling distribution of the sample mean can be approximated closely by a
normal curve
D. if n is large, then the variance of the sample must be small
9. Changing the o of a distribution does what to the probability density function?
A. Shifts the distribution on the vertical axis
B. Determines the shape of the distribution
C. Shifts the distribution on the horizontal axis
D. None of the above
10. The Central Limit Theorem is important in Statistics because:
A. it tells us that population does not need to be collected
B. it guarantees that, when it applies, the samples that are drawn are always randomly selected
C. it enables reasonably accurate probabilities to be determined for events involving the sample average
when the sample size is large regardless of the distribution of the variable
D. it tells us that if all the possible combination samples have produced sample average will likely be
close to its expected value
11. Which of the following best describes the a-level in statistical testing?
A. The threshold for significance, usually set equal to 0.05
B. The Type II error rate
C. Arithmetically equal to 1- (Type II error rate)
D. The probability of type I error

Transcribed Image Text:12. Which of the following is a key difference between the t distribution with degrees of freedom X, and
the standard normal?
A. The standard normal will not always have a higher peak about the mean.
B. The t distribution will always have a higher peak about the mean.
C. The t distribution typically has a smaller area near the tails of the distribution.
D. The t distribution typically has a larger area near the mean of the distribution.
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