Standard errors are statistical measures that estimate the accuracy of a sample statistic as an approximation of the population parameter. They indicate how much variability can be expected in sample estimates due to sampling error, which is the difference between the sample value and the true population value. Understanding standard errors is crucial for hypothesis testing and constructing confidence intervals, particularly when applying techniques like Chow tests to assess structural changes in regression models.
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