Interval estimation is a statistical technique used to estimate a range within which a population parameter is expected to lie, with a specified level of confidence. It provides more informative insights than point estimation by accounting for sampling variability and uncertainty in the data.

Interval Estimation

Interval estimation

statistical technique

A population parameter is a numerical value that describes a characteristic of a population, such as a mean or standard deviation, and is often unknown and estimated through sample statistics. Understanding population parameters is crucial for making inferences about the entire population based on sample data, which is a fundamental aspect of inferential statistics.

population parameter

specified level of confidence

Point estimation is a statistical technique used to provide a single best guess or estimate of an unknown population parameter based on sample data. It aims to derive specific values, such as the mean or variance, which are considered the most representative of the underlying population characteristic being studied.

point estimation

Sampling variability refers to the natural fluctuations in statistical estimates that occur when different random samples are drawn from the same population. It highlights the importance of using larger sample sizes and appropriate sampling techniques to ensure the reliability and accuracy of statistical inferences.

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