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The 19 pages that link to Standard error, each with the reason it gives.

• Confidence intervalRelated: It measures the sampling uncertainty that determines an interval’s width.

• Sampling distributionRelated: It measures the spread of this distribution and typically shrinks as sample size increases.

• Central limit theoremRelated: For sample means, the theorem motivates the familiar standard-error scale.

• Standard deviationRelated: It distinguishes uncertainty in an estimated mean from spread among individual observations.

• Sampling errorRelated: It measures the typical size of sampling variation for an estimator.

• EconometricsRelated: Standard errors quantify uncertainty in econometric estimates and support statistical tests.

• Parameter estimationRelated: It quantifies uncertainty in an estimate caused by finite data.

• Student's t-distributionRelated: The t-statistic divides a mean's deviation by an estimated standard error.

• Margin of errorRelated: The margin is often calculated by multiplying a standard error by a critical value.

• Sample meanRelated: It measures how much the sample mean typically varies across repeated samples.

• Sample sizeRelated: For many estimates, standard error decreases roughly with the square root of sample size.

• MulticollinearityRelated: Multicollinearity often enlarges coefficient standard errors without greatly changing fitted predictions.

• Prediction intervalRelated: Uncertainty in the estimated mean contributes to prediction interval width.

• Student's t-testRelated: The mean difference is scaled by its standard error to form the t-statistic.

• Sample (statistics)Related: It quantifies the uncertainty caused by using a sample.

• Frequentist inferenceRelated: It quantifies the repeated-sample variability used to calibrate tests and intervals.

• Mathematical statisticsRelated: It expresses the sampling uncertainty used in intervals and hypothesis tests.

• Sample size determinationRelated: It connects sample size to the expected variability of estimates.

• Bienaymé's identityRelated: Variances of independent observations add when calculating uncertainty in sums and averages.