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. It is expressed with a certain level of confidence, such as 90%, 95%, or 99%, indicating the probability that the interval includes the parameter. Wider intervals suggest more uncertainty about the parameter's exact value.
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Level of Confidence
The level of confidence represents the degree of certainty that the confidence interval contains the true population parameter. Common levels include 90%, 95%, and 99%. A higher level of confidence means that the interval is constructed to be wider, as it accounts for more variability and uncertainty in the data.
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Introduction to Confidence Intervals
Critical Value
The critical value is a factor used to calculate the margin of error in a confidence interval. It is derived from the standard normal distribution (Z-distribution) or t-distribution, depending on the sample size and whether the population standard deviation is known. As the level of confidence increases, the critical value also increases, leading to a wider confidence interval.
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