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 with a specified level of confidence. For example, a 99% confidence interval suggests that if we were to take many samples and construct intervals in the same way, approximately 99% of those intervals would contain the true population mean.
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Normal Distribution
Normal distribution is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. In constructing confidence intervals, it is often assumed that the population from which the sample is drawn is normally distributed, especially when the sample size is small.
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Sample Mean and Standard Deviation
The sample mean is the average of a set of values, calculated by summing all the observations and dividing by the number of observations. The sample standard deviation measures the amount of variation or dispersion in a set of values. Both the sample mean and standard deviation are crucial for calculating the confidence interval, as they provide the necessary statistics to estimate the range around the population mean.
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