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Do some normal probability distributions have different means and different standard deviations?
Yes. Normal (or Gaussian) distribution are parametric distributions and they are defined by two parameters: the mean and the variance (square of standard deviation). Each pair of these parameters gives rise to a different normal distribution. However, they can all be "re-parametrised" to the standard normal distribution using z-transformations. The standard normal distribution has mean 0 and variance 1.
What else can I help you with?
Do normal probability distributions have different arithmetic means and different standard deviations?
Yes. And that is true of most probability distributions.
Do some normal probability distributions have different arithmetic means and different standard deviations?
Yes. Most do.
True or false two normal distributions that have the same mean are centered at the same place regardless of the relationship between their standard deviation?
True. Two normal distributions that have the same mean are centered at the same point on the horizontal axis, regardless of their standard deviations. The standard deviation affects the spread or width of the distributions, but it does not change their center location. Therefore, even with different standard deviations, the distributions will overlap at the mean.
What percentage of observations of a normal distribution is reprented by the mean plus or minus 1.96 standard deviations?
The probability of the mean plus or minus 1.96 standard deviations is 0. The probability that a continuous distribution takes any particular value is always zero. The probability between the mean plus or minus 1.96 standard deviations is 0.95
What requirements are necessary for a normal probability distribution to be a standard normal probability?
For a normal probability distribution to be considered a standard normal probability distribution, it must have a mean of 0 and a standard deviation of 1. This standardization allows for the use of z-scores, which represent the number of standard deviations a data point is from the mean. Any normal distribution can be transformed into a standard normal distribution through the process of standardization.
Do normal probability distributions have different arithmetic means and different standard deviations?
Yes. And that is true of most probability distributions.
Do some normal probability distributions have different arithmetic means and different standard deviations?
Yes. Most do.
True or false two normal distributions that have the same mean are centered at the same place regardless of the relationship between their standard deviation?
True. Two normal distributions that have the same mean are centered at the same point on the horizontal axis, regardless of their standard deviations. The standard deviation affects the spread or width of the distributions, but it does not change their center location. Therefore, even with different standard deviations, the distributions will overlap at the mean.
What percentage of observations of a normal distribution is reprented by the mean plus or minus 1.96 standard deviations?
The probability of the mean plus or minus 1.96 standard deviations is 0. The probability that a continuous distribution takes any particular value is always zero. The probability between the mean plus or minus 1.96 standard deviations is 0.95
What is the probability of an event occurring within 5 standard deviations from the mean?
The probability of an event occurring within 5 standard deviations from the mean is extremely rare, as it falls outside the normal range of outcomes.
Measurements that fall beyond 3 standard deviations from the mean?
They do happen, particularly with very skewed distributions.
How do you find highest standard deviation in given number?
Standard deviations are measures of data distributions. Therefore, a single number cannot have meaningful standard deviation.
What would -2 standard deviation below the mean be?
It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.It would mean that the result was 2 standard deviations above the mean. Depending on the distribution of the variable, it may be possible to attach a probability to this, or more extreme, observations.
What is heteroskadicity?
Finance:When the standard deviations of a variable, monitored over time, are non-constant.Math:An irregular scattering of values in multiple distributions with a comparable scatter of variances.
What is the formula to determine the standard deviation of the resulting normal distribution when adding two normal distributions with different means and standard deviations?
s= bracket n over sigma i (xi-x-)^2 all over n-1 closed bracket ^ 1/2
What requirements are necessary for a normal probability distribution to be a standard normal probability distribution?
The normal distribution, also known as the Gaussian distribution, has a familiar "bell curve" shape and approximates many different naturally occurring distributions over real numbers.
When referring to the normal probability there is not just one there is a family of distributions?
A family that is defined by two parameters: the mean and variance (or standard deviation).
