[R] Website, book, paper, etc. that shows example plots of distributions?
dwinsemius at comcast.net
Fri Feb 13 16:10:25 CET 2009
This is probably the right time to issue a warning about the error of
making transformations on the dependent variable before doing your
analysis. The classic error that newcomers to statistics commit is to
decide that they want to "make their data normal". The assumptions of
most regression methods is that the *errors* need to have the desired
relationship between means and variance, and not that the dependent
variable be "normal". Many times the apparent non-normality will be
"explained" or "captured" by the regression model. Other methods of
modeling non-linear dependence are also available.
I found Harrell's book "Regression Modeling Strategies" to be an
excellent source for alternatives. My copy of V&R's MASS is only the
second edition but chapters 5 & 6 in that edition on linear models
also had examples of using QQ plots on residuals. Checking that text's
website I see that chapters 6 at least is probably similar. They
include the scripts from their chapters along with the MASS package
(installed as part of the VR bundle). My copy is entitled "ch06.r" and
resides in the scripts subdirectory:
On Feb 13, 2009, at 8:11 AM, Jason Rupert wrote:
> Thank you very much. Thank you again regarding the suggestion
> below. I will give that a shot and I guess I've got my work counted
> out for me. I counted 45 different distributions.
> Is the best way to get a QQPlot of each, to run through producing a
> data set for each distribution and then using the qqplot function to
> get a QQplot of the distribution and then compare it with my data
> As you can tell I am not a trained statistician, so any guidance or
> suggested further reading is greatly appreciated.
> I guess I am pretty sure my data is not a normal distribution due to
> doing some of the empirical "Goodness of Fit" tests and comparing
> the QQplot of my data against the QQPlot of a normal distribution
> with the same number of points. I guess the next step is to figure
> out which distribution my data most closely matches.
> Also, I guess I could also fool around and take the log, sqrt, etc.
> of my data and see if it will then more closely resemble a normal
> Thank you again for assisting this novice data analyst who is trying
> to gain a better understanding of the techniques using this powerful
> software package.
> --- On Fri, 2/13/09, Gabor Grothendieck <ggrothendieck at gmail.com>
> From: Gabor Grothendieck <ggrothendieck at gmail.com>
> Subject: Re: [R] Website, book, paper, etc. that shows example plots
> of distributions?
> To: jasonkrupert at yahoo.com
> Cc: R-help at r-project.org
> Date: Friday, February 13, 2009, 5:43 AM
> You can readily create a dynamic display for using qqplot and
> similar functions
> in conjunction with either the playwith or TeachingDemos packages.
> For example, to investigate the effect of the shape parameter in the
> normal distribution on its qqplot relative to the normal distribution:
> playwith(qqnorm(rsn(100, shape = shape)),
> parameters = list(shape = seq(-3, 3, .1)))
> Now move the slider located at the bottom of the window that
> appears and watch the plot change in response to changing
> the shape value.
> You can find more distributions here:
> On Thu, Feb 12, 2009 at 1:04 PM, Jason Rupert <jasonkrupert at yahoo.com>
>> By any chance is any one aware of a website, book, paper, etc. or
> combinations of those sources that show plots of different
>> After reading a pretty good whitepaper I became aware of the
>> benefit of I
> the benefit of doing Q-Q plots and histograms to help assess a
> The whitepaper is called:
>> "Univariate Analysis and Normality Test Using SAS, Stata, and
> SPSS*" , (c) 2002-2008 The Trustees of Indiana University Univariate
> Analysis and Normality Test: 1, Hun Myoung Park
>> Unfortunately the white paper does not provide an extensive amount of
> example distributions plotted using Q-Q plots and histograms, so I
> am curious if
> there is a "portfolio"-type website or other whitepaper shows
> examples of various types of distributions.
>> It would be helpful to see a bunch of Q-Q plots and their associated
> histograms to get an idea of how the distribution looks in
> comparison against
> the Gaussian.
>> I think seeing the plot really helps.
>> Thank you for any insights.
>> [[alternative HTML version deleted]]
>> R-help at r-project.org mailing list
>> PLEASE do read the posting guide
>> and provide commented, minimal, self-contained, reproducible code.
> [[alternative HTML version deleted]]
> R-help at r-project.org mailing list
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
More information about the R-help