Yes. It will increase the standard deviation. You are increasing the number of events that are further away from the mean, and the standard deviation is a measure of how far away the events are from the mean.
The answer depends on greater standard deviation that WHAT!
Mean 0, standard deviation 1.
It is a measure of the spread of the distribution. The greater the standard deviation the more variety there is in the observations.
idk about normal distribution but for Mean "M" = (overall sum of "x") / "n" frequency distribution: 'M' = Overall sum of (' x ' * ' f ') / overall sum of ( ' f ' ) M = Mean x = Mid Point f = frequiency n = number of variables ALL FOR STANDARD DEVIATION * * * * * A general Normal distribution is usually described in terms of its parameters, and given as N(mu, sigma2) where mu is the mean and sigma is the standard deviation. The STANDARD Normal distribution is the N(0, 1) distribution, that is, it has mean = 0 and variance (or standard deviation) = 1.
Standard deviation describes the spread of a distribution around its mean.
The standard deviation in a standard normal distribution is 1.
The standard deviation in a standard normal distribution is 1.
The answer depends on greater standard deviation that WHAT!
Mean 0, standard deviation 1.
It is a measure of the spread of the distribution. The greater the standard deviation the more variety there is in the observations.
Standard deviation describes the spread of a distribution around its mean.
Yes.
idk about normal distribution but for Mean "M" = (overall sum of "x") / "n" frequency distribution: 'M' = Overall sum of (' x ' * ' f ') / overall sum of ( ' f ' ) M = Mean x = Mid Point f = frequiency n = number of variables ALL FOR STANDARD DEVIATION * * * * * A general Normal distribution is usually described in terms of its parameters, and given as N(mu, sigma2) where mu is the mean and sigma is the standard deviation. The STANDARD Normal distribution is the N(0, 1) distribution, that is, it has mean = 0 and variance (or standard deviation) = 1.
If the samples are drawn frm a normal population, when the population standard deviation is unknown and estimated by the sample standard deviation, the sampling distribution of the sample means follow a t-distribution.
The mean of a distribution gives no information about the standard deviation.
It is called a standard normal distribution.
The statement is probably: The mean and standard deviation of a distribution are 55 and 4.33 respectively.