[R] predicting waste per capita - is a gaussian model correct?

Alessandra Bielli b|e|||@@|e@@@ndr@ @end|ng |rom gm@||@com
Mon May 11 03:59:14 CEST 2020


Dear all

First of all apologies for the off-topic question and for not respecting
the other points.
Second, thanks for your advice and opinion I will definitely consult a
statistician.

Regards,

Alessandra

On Sun, May 10, 2020 at 4:57 PM Abby Spurdle <spurdle.a using gmail.com> wrote:

> Well, this is 100% off-topic...
> And I wasn't planning to answer the OP's question.
>
> However, I disagree with your answer.
>
> > There is no requirement that the dependent variable in a "regression"
> type
> > estimation follows a gaussian distribution.
>
> False.
> It's depends on what type of '"regression" type estimation' one uses,
> among other things.
>
> > You need a model of the
> > process and then use an estimation technique to estimate your model.  If
> > effects in your model are additive do not use a log transformation. If
> > effects are multiplicative then use a log transformation.
>
> The main question is, does the model satisfy the *assumptions*.
>
> > The choice
> > should be determined by the mechanics of the problem and not by the
> > statistics.
>
> While a mechanistic understanding is definitely valuable...
> If the criteria for a good model vs a bad model, was whether the model
> was consistent with mechanistic theory/understanding, then nearly
> every statistical model I've seen would be a bad model.
> I would say, a good model is one that is useful...
>
> > If you do use a log transformation the trying to reverse the
> > process using an exponential transformation will be biased.
> > The extent of
> > that bias depends on your problem and it would not be possible to
> estimate
> > the significance of the bias without a much greater knowledge of the
> > process and data.
>
> Never heard of this before...
> But I do note back-transformation is not trivial, and I'm not an
> expert on back-transformations.
>
> > I would suggest that you consult a competent
> > statistician.
>
> I agree on that part...
>

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