when the signals are symmetric then this signals are gaussian In statistics, the Gaussian curve, also known as the Normal curve, is symmetrical.
The Gaussian curve is the Normal distributoin curve, the commonest (and most studied) of statistical distributions.
It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.
Gaussian curve
The bell curve graph is another name for a normal (Gaussian) distribution graph. A Gaussian function is a certain kind of function whose graph results in a bell-shaped curve.
a Gaussian or 'normal' distribution
The probability of getting the exact shape of the Gaussian bell shaped curve is 0. And that is true even if you use a billion dice. The curve from repeated throws of one die, or many dice will approximate the Gaussian curve and the approximation will get better as the number of trails increases.However, the Gaussian curve extends to infinity in both direction and there is a very small but non-zero probability associated with these extreme values. You will not get an outcome that is infinite!
this function is extremely used in probability theory like this bell curve
The term you are probably looking for is a Bell curve, which is a Gaussian distribution.
Excel is considerably easier to learn, but is very limited in its data analysis and graphics. MATLAB has a very steep learning curve, but can do anything you want. Seriously, anything. If this is part of your work or research, I highly recommend learning MATLAB.
If the Z-Score corresponds to the standard deviation, then the distribution is "normal", or Gaussian.
It is assumed that by "shape" you mean "area". The quick answer is yes, probably. The "Bell curve" is called a Gaussian function (see related link). The area under a Gaussian is not necessarily 1; it can be anything. However, if you're talking about probability, where the probability distribution is in the same of a Gaussian, then the area under the curve must be exactly 1. This isn't however, because it is a bell curve, but because it's a probability distribution. The area under any probability distribution must always be exactly 1, or it isn't a valid distribution. The proper term for the total area under any curve f(x) is the integral from negative infinity to infinity of f(x) dx