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 true 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 parameter.
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Introduction to Confidence Intervals
Population Standard Deviation (σ)
The population standard deviation (σ) is a measure of the amount of variation or dispersion in a set of values in a population. It quantifies how much individual data points differ from the population mean. In constructing confidence intervals for σ, we often use sample data to estimate this parameter, which is crucial for understanding the variability of the population.
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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. Many statistical methods, including confidence interval construction, assume that the underlying population is normally distributed, especially when sample sizes are small, as it affects the validity of the results.
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