Standard error

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Standard Error

The Standard Error (pronounced: /ˈstandərd ˈerər/) is a statistical term that measures the accuracy with which a sample represents a population. In statistics, the standard error is the standard deviation of the sampling distribution of a statistic.

Etymology

The term "Standard Error" is derived from the field of statistics. The word "standard" refers to a norm or a rule that is widely accepted and followed. The word "error" refers to the deviation from the truth or the actual value. Thus, the term "Standard Error" refers to the standard deviation of the errors in a set of measurements.

Definition

In Statistics, the Standard Error is used to measure the dispersion or variability of a sampling distribution. It is calculated as the standard deviation of the sample mean divided by the square root of the sample size. The smaller the standard error, the more representative the sample will be of the overall population.

Formula

The formula for calculating the standard error is:

SE = σ / √n

Where:

  • SE is the standard error
  • σ is the standard deviation of the population
  • n is the size of the sample

Related Terms

  • Standard Deviation: A measure of the amount of variation or dispersion of a set of values.
  • Sample Size: The number of observations in a sample.
  • Sampling Distribution: A probability distribution of a statistic obtained through a large number of samples drawn from a specific population.
  • Population: In statistics, a population is the total set of observations that can be made.

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