Foundations of Data Science
A confidence interval is a range of values derived from sample data that is likely to contain the true population parameter with a specified level of confidence, often expressed as a percentage like 95% or 99%. It provides an estimated interval that reflects the uncertainty associated with sampling and helps in making inferences about the population. This concept is closely tied to estimation techniques and hypothesis testing, which help assess the validity of assumptions and make predictions based on data.
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