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

Point estimation

statistical technique

best guess

unknown population parameter

Sample data refers to a subset of data collected from a larger population, used to make inferences or test hypotheses about the entire population. It is crucial in statistical analysis, as it allows researchers to draw conclusions without examining every individual in the population, thereby saving time and resources.

sample data

specific values

The mean, often referred to as the average, is a measure of central tendency that is calculated by summing all the values in a dataset and dividing by the number of values. It provides a useful summary of the data but can be heavily influenced by outliers, making it less representative in skewed distributions.

mean

Variance is a statistical measure that quantifies the dispersion of a set of data points around their mean, providing insight into the degree of spread in the dataset. A higher variance indicates that the data points are more spread out from the mean, while a lower variance suggests they are closer to the mean.

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