摘要：This paper presents the Agresti & Coull Adjusted Wald method for computing confidence intervals and margins of error for common proportion estimates. The presented method is easily implementable by business students and practitioners and provides more accurate estimates of proportions particularly in extreme samples and small sample situations. The proposed method may have particular applications to focus group analysis, industry benchmarking, and destructive testing sampling. The paper discusses a computational strategy and several comparison examples.
关键词：Confidence Intervals;Margin Of Error;Wald;Sampling;Econometrics Education
其他关键词：Confidence Intervals;Margin Of Error;Wald;Sampling;Econometrics Education
