ritzbitzcookie wrote:
I may be smart or stupid, the actual truth is that im always humble to knowledge that I may and will gain. So spill it out because if u have knowledge that I can gain to expand my analytical mind to solve problems and even gain solutions through what I can learn. But I have a question for you all to think about. I don't have the answer and if you do plz post it here. What is the mathematical equation of an average man to take one physical step?
Amen ritz, humbleness is almost next to godliness, if it isn't it should be, right? :wink:
This forum is a cornucopia of some really insightful comments and some truly moronic liberal musings. How many liberal musings are moronic you may ask?
ALL OF THEM, I know I have done the math. :lol: :lol: :lol:
I'll bite, here goes...
You first need to define average for both man and then step but, this will get you there.
"As a slightly more complicated real-life example, the average height for adult men in the United States is about 70 inches, with a standard deviation of around 3 inches. This means that most men (about 68 percent, assuming a normal distribution) have a height within 3 inches of the mean (6773 inches) one standard deviation and almost all men (about 95%) have a height within 6 inches of the mean (6476 inches) two standard deviations. If the standard deviation were zero, then all men would be exactly 70 inches tall. If the standard deviation were 20 inches, then men would have much more variable heights, with a typical range of about 5090 inches. Three standard deviations account for 99.7 percent of the sample population being studied, assuming the distribution is normal (bell-shaped).".
So...
Definition of population valuesLet X be a random variable with mean value μ:
E[X] = μ.
Here the operator E denotes the average or expected value of X. Then the standard deviation of X is the quantity
(derived using the properties of expected value).
In other words the standard deviation σ (sigma) is the square root of the variance of X; i.e., it is the square root of the average value of {X − μ}2.
The standard deviation of a (univariate) probability distribution is the same as that of a random variable having that distribution. Not all random variables have a standard deviation, since these expected values need not exist. For example, the standard deviation of a random variable that follows a Cauchy distribution is undefined because its expected value μ is undefined.
Well heck, you asked right?
I really loathed statistics so, pardon me if I let you calculate the rest. :shock: :shock: :shock:
:wink: :lol: :lol: :lol: :thumbup: