Here are the essential concepts you must grasp in order to answer the question correctly.
Confidence Interval
A confidence interval is a range of values, derived from sample statistics, that is likely to contain the population parameter (like the mean) with a specified level of confidence. For example, a confidence level of 80% means that if we were to take many samples and construct intervals, approximately 80% of those intervals would contain the true population mean.
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Standard Deviation
Standard deviation is a measure of the amount of variation or dispersion in a set of values. In the context of confidence intervals, it helps quantify the uncertainty around the sample mean. A smaller standard deviation indicates that the data points tend to be closer to the mean, leading to a narrower confidence interval.
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Sample Size
Sample size refers to the number of observations in a sample. It plays a crucial role in determining the width of the confidence interval; larger sample sizes generally lead to more precise estimates of the population mean, resulting in narrower confidence intervals. In this case, a sample size of 100 provides a solid basis for estimating the population mean.
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