What is Reddit's opinion of An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements?

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Coincidentally, this is my favorite trainwreck of all time.

Refer to this book, it will most definitely have the answer for you. Refer pages 60-62, I think it is what you are looking for, if not that chapter should have the answer for you.

You need this book.

Until then - the general formula for error propagation in a function q(x, y, z, ....) with uncertainties δx, δy, δz .... is equal to sqrt( (δx*∂q/∂x)^2 + (δy*∂q/∂y)^2 .....)

For your simple case where q = log10(x), δq = δx/(x*ln(10)).

Hope this helps.

It also serves as one of the greatest textbook covers of all time.

Oooo... this image was on the front of my old error analysis book in college. I still have it in my office.

https://www.amazon.com/Introduction-Error-Analysis-Uncertainties-Measurements/dp/093570275X

Someone didn’t calculate their uncertainty correctly!

Taylor’s book on uncertainty propagation was pretty helpful for lab reports: https://www.amazon.com/Introduction-Error-Analysis-Uncertainties-Measurements/dp/093570275X

This is the best book cover picture ever used.

Similarly:

https://www.amazon.com/Introduction-Error-Analysis-Uncertainties-Measurements/dp/093570275X

This pic is on the cover of a famous statistics book.

https://www.amazon.com/Introduction-Error-Analysis-Uncertainties-Measurements/dp/093570275X

https://www.amazon.com/Introduction-Error-Analysis-Uncertainties-Measurements/dp/093570275X

A photo of this is on cover of the Statistics text An Introduction to Error Analysis.

This image is used in one of my all time favorite textbook covers of all time: Introduction to Error Analysis

https://www.amazon.com/Introduction-Error-Analysis-Uncertainties-Measurements/dp/093570275X

We used this book in my intro level physics lab for error analysis.

A lack of this xD: http://www.amazon.com/Introduction-Error-Analysis-Uncertainties-Measurements/dp/093570275X

I first saw it on the cover of this book.

John Taylor did a great job at writing this book, I suggest it as a good read. It is still used in physics classes to this day: https://www.amazon.com/Introduction-Error-Analysis-Uncertainties-Measurements/dp/093570275X

It boils down to this: Uncertainty in percent is effectively an error.

So if your left leg does 200 Watts (As measured by some mythical leg powermeter device that is 100% accurate) you will get a measurement of +/- 2% from the Stages unit meaning the reading drifts 196 to 204 (left leg only, remember that). Now if you double that (as Stages does) you get a reading of 392-408. This gives you a variance of 4% (assuming left leg power = right leg power).

As for your other question: The claim of accuracy needs to be made about their measurement, not their calculated value. The calculated value (as you have pointed out) is based onan assumption of both legs putting out the same power. You can't account for that in marketing.

I think your question is one of the more interesting and useful questions I have seen on this forum. However, I don't always understand some of the replies posted. Here are some examples: * The Moto X is heavier. Specifications on the websites of “independent” groups list them as within 1 gram of each other in mass. Is someone misrepresenting the product? * The 6P is more "premium". What the heck does this mean? If you choose a plastic back and believe a plastic back is less “premium”, would a different choice have made the difference? My experience with people with iPhones is that my x14 bamboo back is more impressive than a back of aluminum. So is the iPhone less “premium”? (Note - I did not buy another wood back for the X15, but rather a plastic back, because it more secure in the hands.) * The camera is better. That is fine. Other than taking photos without a flash in low light, how is it better? (And why not use the flash?) (For an interesting review related to cameras, see PocketNow’s comparison of the Nexus 5X with the XPE. http://pocketnow.com/2015/10/21/nexus-5x-vs-moto-x-pure-edition ) In short, as an XPE owner, I have no problems if the Nexus 6P has better specifications is, functually, a better device. But I haven’t seen any independent testers provide any reproducible data to support the arguments. I also recommend to people who have both products the Taylor book, “An Introduction to Error Analysis”. http://www.amazon.com/Introduction-Error-Analysis-Uncertainties-Measurements/dp/093570275X

I think OkCupid data is all fair and good. It represents a certain set of people, those that are comfortable with doing online dating on one particular website. Now if we look at the whole population, including those that do not feel the need to use a dating site, we might see a different result.

If you take in account a proper bell curve you'll see that the population of men that are taller than women 5'10 or greater is actually about half the population. so that majority, if one at all, is a small majority. There are two separate bell curves: one for men and one for women. So is it really about a scarcity of suitors; if not, what could it be?

It could be something like men on a certain dating website are intimidated because of previous social interactions skewing the data or a smaller population of tall women on said site. All in all it is more often than not a person making the decision to rule out a specific group.

So, why don't we blame shallow people instead people with a certain physical trait?

Here's a nice book on errors

TL;DR: you don't have data, you have a graph. Shallow people are to blame.