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Answer :
The sampling error, defined as the difference between a population parameter and the sample estimate, is found to be 0.10 in this case.
In this question, we're working with the concept of sampling error in statistics. The sampling error is the difference between a population parameter and the estimate of that parameter derived from a sample. In this case, the population parameter (p) is 0.14 and the sample estimate (ṕ) is 0.24.
To find the sampling error, we subtract the population parameter from the sample estimate. The formula for calculating the sampling error is thus: Sampling Error = ṕ - p.
Therefore, the sampling error in this case is 0.24 - 0.14, which equals 0.10.
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