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A distribution function or a cumulative distribution function. The spread and range are also immediately apparent from a box [and whiskers] plot.
Because very many variables tend to have the Gaussian distribution. Furthermore, even if the underlying distribution is non-Gaussian, the distribution of the means of repeated samples will be Gaussian. As a result, the Gaussian distributions are also referred to as Normal.
Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.
Also normally distributed.
Density is defined as the mass of something divided by the volume of the same thing. During a careful reading of the definition, it becomes apparent that density is not mass, and that density is also similarly not weight as well, either.
The mean of a discrete probability distribution is also called the Expected Value.
A horizon is also called the apparent line that separates the earth from the sky, where they seem to meet.
A distribution function or a cumulative distribution function. The spread and range are also immediately apparent from a box [and whiskers] plot.
A multichannel distribution system can be called a terminal. It can also be called network, an irrigation system, or a depot.
A normal data set is a set of observations from a Gaussian distribution, which is also called the Normal distribution.
Yes, it may change its absolute, and therefore also its apparent, magnitude.Yes, it may change its absolute, and therefore also its apparent, magnitude.Yes, it may change its absolute, and therefore also its apparent, magnitude.Yes, it may change its absolute, and therefore also its apparent, magnitude.
it has a definite volume but no definite shape
Because very many variables tend to have the Gaussian distribution. Furthermore, even if the underlying distribution is non-Gaussian, the distribution of the means of repeated samples will be Gaussian. As a result, the Gaussian distributions are also referred to as Normal.
Power Systems or Transmission & Distribution
According to the Central Limit Theorem the sum of [a sufficiently large number of] independent, identically distributed random variables has a Gaussian distribution. This is true irrespective of the underlying distribution of each individual random variable.As a result, many of the measurable variables that we come across have a Gaussian distribution and consequently, it is also called the normal distribution.According to the Central Limit Theorem the sum of [a sufficiently large number of] independent, identically distributed random variables has a Gaussian distribution. This is true irrespective of the underlying distribution of each individual random variable.As a result, many of the measurable variables that we come across have a Gaussian distribution and consequently, it is also called the normal distribution.According to the Central Limit Theorem the sum of [a sufficiently large number of] independent, identically distributed random variables has a Gaussian distribution. This is true irrespective of the underlying distribution of each individual random variable.As a result, many of the measurable variables that we come across have a Gaussian distribution and consequently, it is also called the normal distribution.According to the Central Limit Theorem the sum of [a sufficiently large number of] independent, identically distributed random variables has a Gaussian distribution. This is true irrespective of the underlying distribution of each individual random variable.As a result, many of the measurable variables that we come across have a Gaussian distribution and consequently, it is also called the normal distribution.
Primary distribution overhead cost is also called Departmentalization of overheads. It involves apportionment and allocation of overhead costs in the service and production departments.
It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.