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Topic: Explanation for why linear regression is a poor fit
Replies: 8   Last Post: Feb 15, 2013 10:36 AM

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Richard Ulrich

Posts: 2,846
Registered: 12/13/04
Re: Explanation for why linear regression is a poor fit
Posted: Feb 4, 2013 7:47 PM
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On Mon, 04 Feb 2013 18:13:22 -0500, Rich Ulrich
<rich.ulrich@comcast.net> wrote:

>On Mon, 4 Feb 2013 12:55:36 -0800 (PST), em.derenne@gmail.com wrote:
>

>>Hi-
>>I haven't taken stats in a few years and recently there have been a lot thrown around my work place, including the attached graph (and raw data). I realize that low R2 mean that the linear regression is not a good fit, but


[snip, rest of post; start of my previous reply]

>The highest 5 outcome scores are all in the first half of the graph,
>and the very highest one is near the beginning. Does that
>seem important? That's most of the effect.
>


I discovered that I can re-format the downloaded chart, even
though it is read-only, in order to show a logarithmic spacing
for the Y axis. The data are pretty well distributed, from a
minimum of 2 to a maximum of 17000.

That gives charts that look a lot like charts in the report that
David Jones gives a link to.... so, taking the log of the measures
does give a *statistical* model that has errors that are much
better behaved, and one that someone else seems to be using
(presuming these are the same data).


>On the other hand, very few people would say that any
>time series is properly tested by a simply linear regression
>when there are autocorrelation effects... which there almost
>always are.
>
>As to the size of the effect, and how few cases it depends
>on -- I'm "pretty sure" that the trend becomes n.s. if you
>remove the top 5 points; "probably" for the top 3, and
>"maybe" for removing the top one alone.


I can imagine that it is a useful statement, to be able to say
that certain REALLY high levels are no longer being reached.
But it needs, I think, a regression on the log-transformed
values in order to make a proper statement on the (lack of)
trend in that pollution control.

--
Rich Ulrich





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