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YMS Ch9: Sampling Distributions AP Statistics at LSHS Mr. Molesky 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Across 3. Greek letter representing the mean of a population 7. A _ distribution describes the values a statistic would take in many repetitions of a sample or experiment under like conditions 9. A number that describes a sample 10. The variability of a statistic is controlled by the _ of the sample. 11.You should only use the formula for the standard deviation of p-hat when the population is 10 times as large as the _ 12. The CLT is the central _ theorem 14. When n is large, the shape of the sampling distribution of p-hat is approximately _ 15. We can use the normal approximation when np and n(1-p) are greater than _ 16. Statistical _ uses data to draw conclusions about the population. Down 1. According to the CLT, the standard deviation of the sampling distribution of x-bar will be sigma divided by the _ _ of the sample size 2. A statistic is _ if the mean of its sampling distribution is equal to the true value of the paramter being estimated. 4. As the sample size gets larger, the variability of the sampling distribution gets _ 5. A number that describes the population 6. Sampling _: The fact that the value of a statistic will vary in repeated sampling 8. The CLT tells us that, regardless of the shape of the population distribution, the shape of the sampling distribution of x-bar will be _ if n is large enough. 10. Another term that describes the variability of a sampling distribution 13. Statistics from _ samples are less variable than statistics from small samples

YMS Ch9: Sampling Distributions

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YMS Ch9: Sampling DistributionsAP Statistics at LSHS

Mr. Molesky1

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Across3. Greek letter representing the mean of a population7. A _ distribution describes the values a statistic would take in many repetitions of a sample or experiment under like conditions9. A number that describes a sample10. The variability of a statistic is controlled by the _ of the sample.11. You should only use the formula for the standard deviation of p-hat when the population is 10 times as large as the _12. The CLT is the central _ theorem14. When n is large, the shape of the sampling distribution of p-hat is approximately _15. We can use the normal approximation when np and n(1-p) are greater than _16. Statistical _ uses data to draw conclusions about the population.

Down1. According to the CLT, the standard deviation of the sampling distribution of x-bar will be sigma divided by the _ _ of the sample size2. A statistic is _ if the mean of its sampling distribution is equal to the true value of the paramter being estimated.4. As the sample size gets larger, the variability of the sampling distribution gets _5. A number that describes the population6. Sampling _: The fact that the value of a statistic will vary in repeated sampling8. The CLT tells us that, regardless of the shape of the population distribution, the shape of the sampling distribution of x-bar will be _ if n is large enough.10. Another term that describes the variability of a sampling distribution13. Statistics from _ samples are less variable than statistics from small samples