Question:
In statistics, standard error measures the:
In statistics, standard error measures the:
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The standard error measures the precision of an estimate, with smaller values indicating higher precision.
Updated On: Sep 24, 2025
- Specification error of the model.
- Autocorrelation in the regression model.
- Correlation between dependent and independent variables.
- Precision of an estimate.
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The Correct Option is D
Solution and Explanation
Step 1: Understanding standard error.
The standard error (SE) is a measure of the precision of an estimate. It quantifies the amount of variation or dispersion of a sample statistic (such as the sample mean) from the population parameter.
Step 2: Analysis of options.
- (A) Specification error of the model: This is incorrect. Specification error refers to mistakes in the model's form, not the precision of the estimate.
- (B) Autocorrelation in the regression model: This is incorrect. Autocorrelation refers to the correlation of residuals across time, not the precision of the estimate.
- (C) Correlation between dependent and independent variables: This is incorrect. Standard error measures the precision, not the correlation.
- (D) Precision of an estimate: This is correct. The standard error quantifies how precise an estimate is, indicating the variability in the sample mean from the population mean.
Step 3: Conclusion.
The correct answer is (D), as standard error measures the precision of an estimate.
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