Carlos,

There are many sources of real datasets (in R itself, on the web), you  
just need to look a little.  For teaching purposes, I think it is  
always better to use real datasets than to use simulated ones.

One thing bothers me, though.  You imply that in all the examples you  
have the data are well fit with linear models, the residuals are  
normal and there is no sign of heteroscedacity.  That sounds a very  
unusual set of examples!

Best

Antony


> From: Roland Rau <roland.rproject@gmail.com>
> Date: 30 May 2008 12:23:17 AM GMT+02:00
> To: Carlos López <natorro@fisica.unam.mx>
> Cc: r-help@r-project.org
> Subject: Re: [R] Datasets in R
>
>
> Carlos López wrote:
>> I´m trying to find datasets that will give me residuals, after  
>> applying the lm function, with no normality, non linearity, and  
>> heteroscedacity so I can try to exemplify
>> those cases in the linear regression model. Can you give any advice  
>> on what datasets would be appropiate? I can´t use the ones in the  
>> alr3 package because those have
>> already been seen in class.
>> Thank you very much :-)
>> natorro
> if you know what you are looking for (or not looking for), wouldn't  
> it be the easiest and fastest thing to do to simulate such a dataset  
> yourself?
>
> Best,
> Roland

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