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According to the Central Limit Theorem, if you take measurements for some variable from repeated samples from any population, the mean values have a probability distribution which is known as the Gaussian distribution. Because of the fact that it is found often it is also called the Normal distribution. It is a symmetric distribution which is fully determined by two parameters: the mean and variance (or standard deviation). It is also sometimes referred to as the bell curve although I have yet to see a bell that stretches out at its bottom towards infinity!

The normal distribution can be used for the heights or masses of people, for examination scores.

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Q: What is the meaning of normal distribution with examples?
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Normal curve is the meaning of standard normal distribution?

No, the normal curve is not the meaning of the Normal distribution: it is one way of representing it.


Real world examples of normal distribution?

normal_distribution


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 normal distribution in statstics?

The normal distribution is a statistical distribution. Many naturally occurring variables follow the normal distribution: examples are peoples' height, weights. The sum of independent, identically distributed variables - whatever their own underlying distribution - will tend towards the normal distribution as the number in the sum increases. This means that the mean of repeated measures of ANY variable will approach the normal distribution. Furthermore, some distributions that are not normal to start with, can be converted to normality through simple transformations of the variable. These characteristics make the normal distribution very important in statistics. See attached link for more.


Why does a researcher want to go from a normal distribution to a standard normal distribution?

A researcher wants to go from a normal distribution to a standard normal distribution because the latter allows him/her to make the correspondence between the area and the probability. Though events in the real world rarely follow a standard normal distribution, z-scores are convenient calculations of area that can be used with any/all normal distributions. Meaning: once a researcher has translated raw data into a standard normal distribution (z-score), he/she can then find its associated probability.


What does theta mean in normal distribution?

There is no particular meaning associated with theta - it will depend on the context.


What is the difference between a normal distribution and the standard normal distribution?

The standard normal distribution is a normal distribution with mean 0 and variance 1.


What is the difference of a normal distribution and a stardard normal distribution?

The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.


Is continuous distribution normal distribution?

le standard normal distribution is a normal distribution who has mean 0 and variance 1


What are some examples of abnormal and normal distribution in statistics?

IQ is normally distributed in the general population. Age is not.


When can you say the distribution is considered normal?

When its probability distribution the standard normal distribution.


Does a normal probability distribution include a bimodal distribution?

No, the normal distribution is strictly unimodal.