ak-77

Isn't that called DEORE?

@mkul7r4: There is no such thing as 'foot shaped'. My feet have almost no arches, narrow heels, a mid-width front foot and a toe line that is highly asymmetric. 5.10 is too wide for me.

@danstonQ: I'm running metal pedals from bike-discount.de home brand Katana. Not much more expensive and I really like them.

@Snfoilhat: To answer your comment: a t test certainly can give you probabilities that your hypothesis is *supported* by the data. If (and even in real scientific articles that is a big if) your measured quantity is directly related to your scientific hypothesis. Even then, a hypothesis that is supported by the data doesn't have to be true. It's just not wrong in a way that would produce different data. And fyi, p=0.06 is indeed not closer to supporting the hypothesis than p=0.01, you have that right, because lower p values indicate a *higher* statistical significance. The papers that you link have to be seen in the context of a trend in certain fields of science, where the focus of researchers has shifted too much to only concentrating on finding differences in datasets that have low p values, without paying enough attention to what those numbers actually tell you about the thing you wanted to investigate in the first place. E.g. in this case, if the hypothesis is: "rear wheel angular velocity that is much smaller than front wheel angular velocity is more likely with worn tires than with fresh ones" , it can be reasonably well tested with a statistical comparison between two data sets of relative velocities. Of course, if you take tighter turns, your relative angular velocity also goes down so that doesn't prove much about traction. Let's put things into perspective here. This guy is doing a t-test with a sample size of 3. Good luck getting significance on anything that isn't bloody obvious beforehand with that sample size. This is a nice piece of quasi-scientific entertainment. That's fine. It's fun to watch. But if we want to do a solid investigation of tire traction, we should not even be discussing p values here. This is engineering, not medicine. You're not limited by the number of healthy volunteers that will take your untested medicine. Go find a long straight fireroad and do a couple hundred braking exercises per tire with rear wheel brake only. Quantify slip with high enough time resolution to actually see the slip/wheel lock up events. Quantify deceleration. Show me histograms, not p values.

@rojo-1: I think the experimental setup is a little too complex, riding the trail is fun but not very controlled. It would have been much more straightforward to measure distance to full stop under maximum braking. You could compare the distance, but also measure slip.

@Snfoilhat: yes, it is literally 'a relationship like smaller number more confidence'. The p value means: 'the probability that your two datasets are random samples from identical distributions is p.' So the lower the p value, the higher the confidence that your differences are not random nut come from two different distributions. When it's not random, the difference has a meaning, in other words, it is significant. How low the probability has to be before you decide it's low enough, depends on the field you are in. 5% is enough for medicine, but doesn't even get close in particle physics. Of course, that is just statistics. Systematic errors, poor design of the experiment and wrong assumptions about the data are independent from this.

@justinfoil: actually, 1m/s is 3.6 kmh so 10 mph=16kmh=4.4 m/s.

@solephaedrus: It's a Dutch word indeed, which can also be translated as 'migration'.

@WhateverBikes: I hear ya. This is why I usually don't use my bell when coming up behind people. Most of the time it makes them look behind and swerve left just as I am about to pass.

@AndrewFleming: dunno how bankruptcy is handled in the US, but around here there's always someone appointed to make sure anything that is still of value is sold off at the best price achievable so the debtors can att least get some money back.