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The mean, median, and mode of a normal distribution are equal; in this case, 22. The standard deviation has no bearing on this question.

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A normal distribution can have any mean and any positive standard deviation?

Yes.


Is normal distribution symmetrical?

Yes. By definition. A normal distribution has a bell-shaped density curve described by its mean and standard deviation. The density curve is symmetrical(i.e., an exact reflection of form on opposite sides of a dividing line), and centered about (divided by) its mean, with its spread (width) determined by its standard deviation. Additionally, the mean, median, and mode of the distribution are equal and located at the peak (i.e., height of the curve).


What is the z value for a normal distribution?

If a random variable X has a Normal distribution with mean m and standard deviation s, then z = (X - m)/s has a Standard Normal distribution. That is, Z has a Normal distribution with mean 0 and standard deviation 1. Probabilities for a general Normal distribution are extremely difficult to obtain but values for the Standard Normal have been calculated numerically and are widely tabulated. The z-transformation is, therefore, used to evaluate probabilities for Normally distributed random variables.


How is it possible to convert normal distributions to the standard normal distribution?

use this link http://www.ltcconline.net/greenl/Courses/201/probdist/zScore.htm Say you start with 1000 observations from a standard normal distribution. Then the mean is 0 and the standard deviation is 1, ignoring sample error. If you multiply every observation by Beta and add Alpha, then the new results will have a mean of Alpha and a standard deviation of Beta. Or, do the reverse. Start with a normal distribution with mean Alpha and standard deviation Beta. Subtract Alpha from all observations and divide by Beta and you wind up with the standard normal distribution.


When the population standard deviation is unknown the sampling distribution is equal to what?

The answer will depend on the underlying distribution for the variable. You may not simply assume that the distribution is normal.

Related Questions

What is the standard deviation of a standard normal distribution?

The standard deviation in a standard normal distribution is 1.


In the standard normal distribution the standard deviation is always what?

The standard deviation in a standard normal distribution is 1.


How does standard normal distribution differ from normal distribution?

The standard normal distribution has a mean of 0 and a standard deviation of 1.


Which normal distribution is also the standard normal curve?

The normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.


A standard normal distribution has a mean of and standard deviation of?

Mean 0, standard deviation 1.


What is Normal of Standard Normal Probability Distribution?

with mean of and standard deviation of 1.


In your own words describe the standard normal distribution?

The standard normal distribution is a special case normal distribution, which has a mean of zero and a standard deviation of one.


What is the distribution with an means of 0 and a standard deviation of 1?

It is called a standard normal distribution.


When the population standard deviation is known the sampling distribution is a?

normal distribution


Is the standard normal distribution has a mean of 1 and standard deviation of 0?

No.


Find z score for normal distribution for 50th percentile?

Answer: 0 The z score is the value of the random variable associated with the standardized normal distribution (mean = 0, standard deviation =1). Now, the median and the mean of a normal distribution are the same. The 50 percentile z score = the median = mean = 0.


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.