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What else can I help you with?
How do you find normal distribution of z-scores?
z-scores are distributed according to the standard normal distribution. That is, with the parameters: mean 0 and variance 1.
Does this means that all symmetric distribution are normal Explain?
Don't know what "this" is, but all symmetric distributions are not normal. There are many distributions, discrete and continuous that are not normal. The uniform or binomial distributions are examples of discrete symmetric distibutions that are not normal. The uniform and the beta distribution with equal parameters are examples of a continuous distribution that is not normal. The uniform distribution can be discrete or continuous.
What is the Difference between normal and gaussian distribution?
Actually the normal distribution is the sub form of Gaussian distribution.Gaussian distribution have 2 parameters, mean and variance.When there is zero mean and unit variance the Gaussian distribution becomes normal other wise it is pronounced as Gaussian.Wrong! The standard normal distribution has mean 0 and variance 1, but a normal distribution is the same as the Gaussiand, and can have any mean and variance. Google stackexcange "what-is-the-difference-between-a-normal-and-a-gaussian-distribution"
What is the purpose of doing the z-score?
The Normal distribution is frequntly encountered in real life. Often a matter of interest is how likely it is that the random variable (RV) being studied takes a value that it did or one that is more extreme. This requires a comparison of the observed value of the RV with its Normal distribution. Unfortunately, the general Normal distribution is extremely difficult to calculate. The Normal distribution is defined by two parameters: the mean and the variance (or standard deviation). It is impossible to tabulate the distribution of every possible combination of two parameters - both of which are continuous real numbers. However, using Z score reduces the problem to that of tabulating only one the Normal distribution: the N(0, 1) or standard Normal distribution. This allows the analysis of an RV with any Normal distribution.
What does it mean for a population to be normally distributed?
A Gaussian distribution is the "official" term for the Normal distribution. This is a probability density function, of the exponential family, defined by the two parameters, its mean and variance. A population is said to be normally distributed if the values that a variable of interest can take have a normal or Gaussian distribution within that population.
Why Normal distribution is better then other distributions in statistics?
The normal distribution has two parameters, the mean and the standard deviation Once we know these parameters, we know everything we need to know about a particular normal distribution. This is a very nice feature for a distribution to have. Also, the mean, median and mode are all the same in the normal distribution. Also, the normal distribution is important in the central limit theorem. These and many other facts make the normal distribution a nice distribution to have in statistics.
What is the difference bitween normal distrubution and standard normal distribution?
A normal distribution is defined by two parameters: the mean, m, and the variance s2, (or standard deviation, s).The standard normal distribution is the special case of the normal distribution in which m = 0 and s = 1.
How do you find normal distribution of z-scores?
z-scores are distributed according to the standard normal distribution. That is, with the parameters: mean 0 and variance 1.
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 studies use parametric statistics?
to estimate the parameter values of a known distribution like normal distribution in this we estimate the parameters pop.mean and s.d
What are the two parameters that completely characterize a standarized normal distribution and mean and standard deviation?
mode and skew
What are the two parameters that are necessary to determine probabilities for a particular normal distribution curve?
Mean and Standard Deviation
Does this means that all symmetric distribution are normal Explain?
Don't know what "this" is, but all symmetric distributions are not normal. There are many distributions, discrete and continuous that are not normal. The uniform or binomial distributions are examples of discrete symmetric distibutions that are not normal. The uniform and the beta distribution with equal parameters are examples of a continuous distribution that is not normal. The uniform distribution can be discrete or continuous.
What is the Difference between normal and gaussian distribution?
Actually the normal distribution is the sub form of Gaussian distribution.Gaussian distribution have 2 parameters, mean and variance.When there is zero mean and unit variance the Gaussian distribution becomes normal other wise it is pronounced as Gaussian.Wrong! The standard normal distribution has mean 0 and variance 1, but a normal distribution is the same as the Gaussiand, and can have any mean and variance. Google stackexcange "what-is-the-difference-between-a-normal-and-a-gaussian-distribution"
What is the purpose of doing the z-score?
The Normal distribution is frequntly encountered in real life. Often a matter of interest is how likely it is that the random variable (RV) being studied takes a value that it did or one that is more extreme. This requires a comparison of the observed value of the RV with its Normal distribution. Unfortunately, the general Normal distribution is extremely difficult to calculate. The Normal distribution is defined by two parameters: the mean and the variance (or standard deviation). It is impossible to tabulate the distribution of every possible combination of two parameters - both of which are continuous real numbers. However, using Z score reduces the problem to that of tabulating only one the Normal distribution: the N(0, 1) or standard Normal distribution. This allows the analysis of an RV with any Normal distribution.
What does normal mean in a science way?
In science, "normal" typically means something that is within expected parameters or conforms to a standard. For example, a "normal distribution" refers to a bell-shaped curve that represents the expected distribution of a set of data points.
Is the normal distribution always being defined by the mean and standard deviation?
Yes, the normal distribution is uniquely defined by its mean and standard deviation. The mean determines the center of the distribution, while the standard deviation indicates the spread or dispersion of the data. Together, these two parameters specify the shape and location of the normal distribution curve.
