A quantile-quantile plot (Q-Q plot) is a graphical tool that compares a data distribution and a specified probability distribution. If the points in a Q-Q plot appear to fall on a straight line, that is evidence that the data can be approximately modeled by the target distribution. Although it is
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When I fill up my daily-driver Prius, the price of gasoline isn't that important. But when I occasionally take a trip in my V8 Suburban, I pay a lot more attention! Therefore I was pleasantly surprised when I noticed that gasoline prices have been...
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Now is your chance to learn even more about SAS hash tables with four additional articles on the subject.
The post Four more tips about hash tables appeared first on SAS Learning Post.
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When you overlay two series in PROC SGPLOT, you can either plot both series on the same axis or you can assign one series to the main axis (Y) and another to a secondary axis (Y2). If you use the Y and Y2 axes,...
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New to SAS? Here are tips from the translator of The Little SAS Book, Fifth Edition. Hongqiu Gu, Ph.D. works at the China National Clinical Research Center for Neurological Diseases at the National Center for Healthcare Quality Management in Neurological Diseases at Beijing Tiantan...
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Recently The Little SAS Book reached a major milestone. For the first time ever, it was translated into another language. The language in this case was Chinese, and the translator was Hongqiu Gu, Ph.D. from the China National Clinical Research Center for Neurological Diseases...
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Does this situation sound familiar? You have a complex analysis that must be finished urgently. The data was delivered late and its quality and structure are far from the expected standard. The time pressure to present the results is huge, and your SAS...
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Numbers don't lie, but sometimes they don't reveal the full story. Last week I wrote about the most popular articles from The DO Loop in 2018. The popular articles are inevitably about elementary topics in SAS programming or statistics because those topics have broad...
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Deming regression (also called errors-in-variables regression) is a total regression method that fits a regression line when the measurements of both the explanatory variable (X) and the response variable (Y) are assumed to be subject to normally distributed errors. Recall that in ordinary least...
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