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Is every normal distribution defined for all real numbers?
Yes.
Real life example of normal distribution?
The height of adult males in your nearest town.
What is the relationship between the Z-score for Normal Distribution and Continuous Probability?
There is no real relationship. Probabilities for the Normal distribution are extremely difficult to work out. The z-score is a method used to convert any Normal distribution into the Standard Normal distribution so that its probabilities can be looked up in tables easily. There are infinitely many types of continuous probability distributions and the Normal is just one of them.
What is the difference between a general normal curve and a standard normal curve?
A standard normal distribution has a mean of zero and a standard deviation of 1. A normal distribution can have any real number as a mean and the standard deviation must be greater than zero.
What are examples of intersecting lines in the real world?
Roads are an example of intersecting lines in the real world.
What properties distinguishes standard normal distribution from other normal distribution?
The normal distribution can have any real number as mean and any positive number as variance. The mean of the standard normal distribution is 0 and its variance is 1.
How many possible outcomes for normal distribution?
Infinitely many. The normal distribution is applicable to a continuous variable whose domain is the whole of the real numbers. Infinitely many. The normal distribution is applicable to a continuous variable whose domain is the whole of the real numbers. Infinitely many. The normal distribution is applicable to a continuous variable whose domain is the whole of the real numbers. Infinitely many. The normal distribution is applicable to a continuous variable whose domain is the whole of the real numbers.
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.
How normal distribution is better?
Normal distribution is not "better." It is, perhaps, simpler to work with. All introductory text books and courses on statistics cover it in great detail, its properties are well-known, and there are lots of tables you can refer to. But if the real-world situation you are trying to model does not resemble a normal distribution, then it is very bad to try to use the properties of a normal distribution or to try to force a normal distribution on your data. Doing so will give you inaccurate answers.
Why is it necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution?
It is necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution because the normal distribution contains real observations, while the binomial distribution contains integer observations.
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.
Is every normal distribution defined for all real numbers?
Yes.
Why two tail of normal distribution do not touch the horizontal axis?
The domain of the Normal distribution is the whole of the real line. As a result the horizontal axis is asymptotic to the Normal distribution curve. The curve gets closer and closer to the axis but never, ever reaches it.
Real life example of normal distribution?
The height of adult males in your nearest town.
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 is the difference between a normal distribution and a standard normal distribution?
when you doesnt have information about the real mean of a population and use the estimation of mean instead of the real mean , usually you use t distribution instead of normal distribution. * * * * * Intersting but nothing to do with the question! If a random variable X is distributed Normally with mean m and standard deviation s, then Z = (X-m)/s has a standard Normal distribution. Z has mean 0 and standard deviation = 1 (or Variance = sd2 = 1).
What is the relationship between the Z-score for Normal Distribution and Continuous Probability?
There is no real relationship. Probabilities for the Normal distribution are extremely difficult to work out. The z-score is a method used to convert any Normal distribution into the Standard Normal distribution so that its probabilities can be looked up in tables easily. There are infinitely many types of continuous probability distributions and the Normal is just one of them.
