Thanks for the feedback. Confirming your replies below:

On Sun, Mar 30, 2014 at 4:59 PM, Raul Miller <[email protected]> wrote:

>
> Sure you didn't mean for one of those to be distance driven?
>
>
Yes, sorry, the columns are:

Period, Car, Hours, Miles, Total Cost

In this example, the car is logging trip start & end time (Hours). It's
logging the # of miles driven. Let's assume the car is getting fueled up
after each trip, so we know the cost.



> Not to mention a 25% reduction in cars...
>
> Yes, I don't think the reduction in cars matters here though


> I'd be tempted to set up a variety of simple models for cost, assume a
> linear correlation and then use %. to see what kinds of numbers I get from
> those.
>
Models might be:
>
> constant cost
> linear cost based on speed
> cost based on square of speed
> cost based distance driven
> cost based on mpg
>

This is somewhat similar to the path I was starting to go down. I'm not
exactly sure how to make your suggestions actionable yet in terms of a
model. If it's relatively simple to explain, I would be very interested
(and others may be too).

I was either going to:
1. Calculate the would-be cost by hold each variable constant. Example:
calculate the cost if the the miles were the same and the speed were the
same and then changing one at a time.

2. Calculate the impact by the ratio of each change -- assuming each are
linear and on the same scale. 10% reduction in miles should be a 10%
reduction in cost assuming MPH is held constant... Something like that


I'll keep thinking and welcome all other ideas

I have some crude code started here too that's using inverted tables:
https://gist.github.com/joebo/fd61043076beafeace30 , just to make it more
concrete
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