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How the normal distribution could be transformed to a standard normal distribution?
Wiki User
∙ 14y ago
You may transform a normal distribution curve, with, f(x), distributed normally, with mean mu, and standard deviation s, into a standard normal distribution f(z), with mu=0 and s=1, using this transform: z = (x- mu)/s
Wiki User
∙ 14y ago
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Is it possible for sample not normal to be from normal population?
Yes. You could have a biased sample. Its distribution would not necessarily match the distribution of the parent population.
Why is the Normal Distribution called normal?
Suppose you could call it the Gaussian Distribution or the Laplace-Gauss (not to be confused with the Laplace distribution which takes an absolute difference from the mean rather than a squared error)... however the Brits had no one to name this distribution after (not the German and French names) and because it is the ubiquitous distribution they just called it... well the NORMAL!!
How would the mean and standard deviation change if the largest data in each set were removed?
Yes. The standard deviation and mean would be less. How much less would depend on the sample size, the distribution that the sample was taken from (parent distribution) and the parameters of the parent distribution. The affect on the sampling distribution of the mean and standard deviation could easily be identified by Monte Carlo simulation.
What is the standard normal distribution for the area to the left of z-1.72 and show work?
Area to the left of z = -1.72 = area to the right of z = 1.72 That is ALL the "working" that you will be able to show - unless you are into some serious high level mathematics. Most school teachers and many university lecturers will not be able to integrate the standard normal distribution: they will look it up in tables. (I have an MSc in Mathematical Statistics and I could do it but not without difficulty). Pr(z < -1.72) = 0.042716
What is the relationship between standard deviation and accuracy?
It depends what you're asking. The question is extremely unclear. Accuracy of what exactly? Even in the realm of statistics an entire book could be written to address such an ambiguous question (to answer a myriad of possible questions). If you simply are asking what the relationship between the probability that something will occur given the know distribution of outcomes (such as a normal distribution), the mean of that that distribution, and the the standard deviation, then the standard deviation as a represents the spread of the curve of probability. This means that if you had a cure where 0 was the mean, and 3 was the standard deviation, the likelihood of observing a value of 12 (or -12) would be likely inaccurate if that was your prediction. However, if you had a mean of 0 and a standard deviation of 100, the likelihood of observing of a 12 (or -12) would be quite likely. This is simply because the standard deviation provides a simple representation of the horizontal spread of probability on the x-axis.
What is the perfect standard normal distribution?
The standard normal distribution is a subset of a normal distribution. It has the properties of mean equal to zero and a standard deviation equal to one. There is only one standard normal distribution and no others so it could be considered the "perfect" one.
What is the standard deviation of the mean of 9.65?
It depends on what the distribution is. In a Normal or Gaussian distribution, the standard deviation is the square root of the mean, so it could be 3.1 but, again, it depends on the distribution.
What is four sigma?
It could refer to four standard errors. If an observation from a Gaussian (normal) distribution is 4 standard errors away from the mean, it has an extremely low probability.
What is the math shape when it looks like a bow?
It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.
How do you find the semi-interquartile range with only the mean and standard deviation?
In general, you cannot. If the distribution can be assumed to be Gaussian [Normal] then you could use z-scores.
Is it possible for sample not normal to be from normal population?
Yes. You could have a biased sample. Its distribution would not necessarily match the distribution of the parent population.
Why is the Normal Distribution called normal?
Suppose you could call it the Gaussian Distribution or the Laplace-Gauss (not to be confused with the Laplace distribution which takes an absolute difference from the mean rather than a squared error)... however the Brits had no one to name this distribution after (not the German and French names) and because it is the ubiquitous distribution they just called it... well the NORMAL!!
How do you calculate standard deviation without a normal distribution?
You calculate standard deviation the same way as always. You find the mean, and then you sum the squares of the deviations of the samples from the means, divide by N-1, and then take the square root. This has nothing to do with whether you have a normal distribution or not. This is how you calculate sample standard deviation, where the mean is determined along with the standard deviation, and the N-1 factor represents the loss of a degree of freedom in doing so. If you knew the mean a priori, you could calculate standard deviation of the sample, and only use N, instead of N-1.
How would the mean and standard deviation change if the largest data in each set were removed?
Yes. The standard deviation and mean would be less. How much less would depend on the sample size, the distribution that the sample was taken from (parent distribution) and the parameters of the parent distribution. The affect on the sampling distribution of the mean and standard deviation could easily be identified by Monte Carlo simulation.
What is the standard normal distribution for the area to the left of z-1.72 and show work?
Area to the left of z = -1.72 = area to the right of z = 1.72 That is ALL the "working" that you will be able to show - unless you are into some serious high level mathematics. Most school teachers and many university lecturers will not be able to integrate the standard normal distribution: they will look it up in tables. (I have an MSc in Mathematical Statistics and I could do it but not without difficulty). Pr(z < -1.72) = 0.042716
Is A distribution is noticeably bimodal if the means of each distribution are separated by at least one standard deviation?
This could be a bimodal. There are many other factors that would have to be taken into account as well.
What is the relationship between standard deviation and accuracy?
It depends what you're asking. The question is extremely unclear. Accuracy of what exactly? Even in the realm of statistics an entire book could be written to address such an ambiguous question (to answer a myriad of possible questions). If you simply are asking what the relationship between the probability that something will occur given the know distribution of outcomes (such as a normal distribution), the mean of that that distribution, and the the standard deviation, then the standard deviation as a represents the spread of the curve of probability. This means that if you had a cure where 0 was the mean, and 3 was the standard deviation, the likelihood of observing a value of 12 (or -12) would be likely inaccurate if that was your prediction. However, if you had a mean of 0 and a standard deviation of 100, the likelihood of observing of a 12 (or -12) would be quite likely. This is simply because the standard deviation provides a simple representation of the horizontal spread of probability on the x-axis.
