Assuming a normal distribution of incomes: 2672
z = ( 2672 - 3036 ) / 950 = -0.383157895
Pr{z<=-0.383157895}~=0.3508013475 or 35%
The cumulative probability up to the mean plus 1 standard deviation for a Normal distribution - not any distribution - is 84%. The reference is any table (or on-line version) of z-scores for the standard normal distribution.
The standard deviation is the standard deviation! Its calculation requires no assumption.
Are you talking of this in means of Statistics? If you are, then the variation from the mean is measured in standard deviation.
Standard error of the mean (SEM) and standard deviation of the mean is the same thing. However, standard deviation is not the same as the SEM. To obtain SEM from the standard deviation, divide the standard deviation by the square root of the sample size.
difference standard deviation of portfolio
approximately 32nd percentile
A standard deviation in statistics is the amount at which a large number of given values in a set might deviate from the average. A percentile deviation represents this deviation as a percentage of the range.
It depends on the underlying distribution. If Gaussian (standrad normal) then the percentile is 77.
The lower case sigma character (σ) represents standard deviation.
You would be in the 99th percentile (98.61, to be more precise).
The Miller Analogies Test scores have a mean of 400 and a standard deviation of 25, and are approximately normally distributed.z = ( 351.5 - 400 ) / 25 = -1.94That's about the 2.6 percentile.(Used wolframalpha.com with input Pr [x < -1.94] with x normally distributed with mean 0 and standard deviation 1.)
The cumulative probability up to the mean plus 1 standard deviation for a Normal distribution - not any distribution - is 84%. The reference is any table (or on-line version) of z-scores for the standard normal distribution.
The standard deviation is the standard deviation! Its calculation requires no assumption.
The standard deviation of the population. the standard deviation of the population.
Yes, a standard deviation of 4.34 can be correct. Standard deviation is a measure of dispersion or variability in a data set. It represents the average amount by which individual data points deviate from the mean. Therefore, a standard deviation of 4.34 simply indicates that there is some variability in the data, with data points on average deviating by 4.34 units from the mean.
The standard deviation is 0.
Information is not sufficient to find mean deviation and standard deviation.