Quote:
Originally Posted by Old Tele man
...can't "explain" ALL the variances, but these 'variables' came to mind:
• differences in wind velocity
• differences in wind direction
• differences in driver control (we're seldom 100% repeatable)
• differences in air temperature
• differences in air density (cold/dry winter vs. hot/humid summer)
• differences in GPS satellite lock-on's (jumping between different satellites?)
...individually, these might be small, but their "interactions" might be significant?!?
...what kind of regression correlation coefficent (R^2) do you get when you tell the Trendline function to "set intercept = 0", which forces the "average" line to go through zero at Y = X = 0.
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Hi Tele,
Yes, I understand what you are saying about "influences" that could affect the coast down numbers.
I absolutely agree that wind and temperature have affected the repeatability of these number presented, and I have made no attempt to correlate them with individual coast down decelerations towards the end of this study.
Why?
The GPS readings are simply too few, and littered with too much scatter.
I have probably spent well over 200 hours or so "trying" to get more stable or properly "filtered" data from the raw GPS output. All in vain in my opinion however. The GPS data is simply too scattered to be of much use for this precision application.
As for the statistical R^2 value, in this case I think that "goodness of fit" number is of not much use with this much data variation.
As for the Instuctables.com posting, you can now see that much more data needs to be collected to get really accurate results.
Jim