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Are all variables that are approximentaly normally distributed be transformed to standard normal variables?
Wiki User
∙ 10y ago
Yes, to approximately standard normal.
If the random variable X is approximately normal with mean m and standard deviation s, then
(X - m)/s
is approximately standard normal.
Wiki User
∙ 10y ago
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How to present a variable that is not normally distributed?
There are many variables that are not normally distributed. You can describe them using a probability distribution function or its cumulative version; you can present them graphically.
Is a normally distributed variable needed to have a normally distributed sampling distribution.?
Yes, it is.
When do you use a normal distribution?
When studying the sum (or average) of a large number of independent variables. A large number is necessary for the Central Limit Theorem to kick in - unless the variables themselves were normally distributed. Independence is critical. If they are not, normality may not be assumed.
How do you assess if data is normally distributed?
The easiest way to tell if data is normally distributed is to plot the data.line plot apex
Scores on an examination are assumed to be?
Normally distributed.
What is the The sum of two normally distributed random variables?
The sum of two random variables that are normally distributed will be also be normally distributed. Use the link and check out the article. It'll save a cut and paste.
Does a population have to be normally distributed in order to use the chi-square distribution?
No, but the approximation is better for normally distributed variables.
ARE All continuous random variables are normally distributed?
YES.
How to present a variable that is not normally distributed?
There are many variables that are not normally distributed. You can describe them using a probability distribution function or its cumulative version; you can present them graphically.
Will the sum of two normally distributed random variables be normally distributed if the random variables are independent?
Yes, and the new distribution has a mean equal to the sum of the means of the two distribution and a variance equal to the sum of the variances of the two distributions. The proof of this is found in Probability and Statistics by DeGroot, Third Edition, page 275.
How chi square distribution is extension of normal distribution?
Given "n" random variables, normally distributed, and the squared values of these RV are summed, the resultant random variable is chi-squared distributed, with degrees of freedom, k = n-1. As k goes to infinity, the resulant RV becomes normally distributed. See link.
Is a normally distributed variable needed to have a normally distributed sampling distribution.?
Yes, it is.
What does the Central Limit Theorem state?
The Central Limit Theorem (abbreviated as CLT) states that random variables that are independent of each other will have a normally distributed mean.
Can you think of a variable that is normally distributed?
The value of a roll of two dice is normally distributed.
When do you use a normal distribution?
When studying the sum (or average) of a large number of independent variables. A large number is necessary for the Central Limit Theorem to kick in - unless the variables themselves were normally distributed. Independence is critical. If they are not, normality may not be assumed.
Scores on an examination are assumed to be normally?
...normally distributed.
Is weight normally distributed?
NO!
