2017
DOI: 10.1080/03610918.2016.1165840
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Normal probability plots with confidence for the residuals in linear regression

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Cited by 4 publications
(2 citation statements)
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“…In the normal probability plot the data doesn't fit a straight line and this verified that the residuals in the data were not normally distributed. In the normal probability plot of the effects, that are farther from 0 are statistically significant (Chantarangsi et al, 2016). The color and shape of the points differ between statistically significant and statistically Surface plot is a plot that shows the 3D model of contour plot.…”
Section: Optimization Of Siderophore Production and Statistical Analysis Of The Ccd (By Rsm And Anova)mentioning
confidence: 99%
“…In the normal probability plot the data doesn't fit a straight line and this verified that the residuals in the data were not normally distributed. In the normal probability plot of the effects, that are farther from 0 are statistically significant (Chantarangsi et al, 2016). The color and shape of the points differ between statistically significant and statistically Surface plot is a plot that shows the 3D model of contour plot.…”
Section: Optimization Of Siderophore Production and Statistical Analysis Of The Ccd (By Rsm And Anova)mentioning
confidence: 99%
“…The normal probability plot shows the distribution of the residual value, which is defined as the difference between the predicted (model) and observed (experimental) values. From the normal probability plot, the population is claimed not to be normally distributed if, and only if, the n points do not fall close to a straight line [63].…”
Section: Simplex Lattice Design-model Establishmentmentioning
confidence: 99%