a) The size of the sampling error that comes from a random sample depends on both the variation in the population and the size of the sample being selected. b) If you increase your sample size, the sample mean will always get closer to the population mean c) Sampling error is the difference between the sample statistic and the population parameter d) If a sample is selected using random sampling methods, the primary reason that the sample mean might be different from the corresponding population mean is that the sample might be biased.

A First Course in Probability (10th Edition)
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Chapter1: Combinatorial Analysis
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Please answer the following questions. Show your work.

 

4. A 90% confidence interval for the mean number of children per family in Chicago is [1.35, 5.23]. Determine whether each statement is true or false. 

a) The probability that  is between 1.35 and 5.23 is 0.90.

b) 90% of all samples should have  between 1.35 and 5.23.

c) We are 90% confident that the true mean number of children per Bay Area family is between 1.35 and 5.23.

d) 90% of all Bay Area families have between 1.35 and 5.23 kids.

 

3. See Attached image. Problem starts with, "The size of the sampling error..."

a) The size of the sampling error that comes from a random sample depends on both the
variation in the population and the size of the sample being selected.
b) If you increase your sample size, the sample mean will always get closer to the population
mean
c) Sampling error is the difference between the sample statistic and the population parameter.
d) If a sample is selected using random sampling methods, the primary reason that the sample
mean might be different from the corresponding population mean is that the sample might be
biased.
e) Sampling error can be eliminated if the sampling is done properly.
f) If we collect twice as much data, our estimates will be twice as precise.
Transcribed Image Text:a) The size of the sampling error that comes from a random sample depends on both the variation in the population and the size of the sample being selected. b) If you increase your sample size, the sample mean will always get closer to the population mean c) Sampling error is the difference between the sample statistic and the population parameter. d) If a sample is selected using random sampling methods, the primary reason that the sample mean might be different from the corresponding population mean is that the sample might be biased. e) Sampling error can be eliminated if the sampling is done properly. f) If we collect twice as much data, our estimates will be twice as precise.
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