The Use and Misuse of Summary Statistics in Regression Analysis

dc.creatorBishop, Robert V.
dc.date2017-04-01T13:58:02Z
dc.date.accessioned2026-07-09T07:04:45Z
dc.descriptionThis article discusses the effect of an autocorrelated error structure on the interpretation of traditional significance tests, especially the t-test and R2 measure It emphasizes first-order serial correlation, a common and often serious problem that researchers using time series data may encounter Even though many of the problems associated with an autocorrelated error structure are well known, many researchers ignore them and report results which range from being potentially misleading to grossly erroneous
dc.identifierdoi:10.22004/ag.econ.148702
dc.identifierhttps://ageconsearch.umn.edu/record/148702/files/3Bishop_33_1.pdf
dc.identifierhttp://ageconsearch.umn.edu/record/148702
dc.identifier.urihttp://hdl.handle.net/123456789/584239
dc.languageeng
dc.publisher
dc.sourcehttp://ageconsearch.umn.edu/record/148702
dc.titleThe Use and Misuse of Summary Statistics in Regression Analysis
dc.typeText

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