a "T" or a "Z" score.
A "T" Score if comparing a sample.
A "Z" Score when comparing a population.
Remember, a population includes all observation, and a sample includes only a random selection of the population.
The standard error is the standard deviation divided by the square root of the sample size.
we calculate standard deviation to find the avg of the difference of all values from mean.,
σ (sigma)
Standard error is the difference between a researcher's actual findings and their expected findings. Standard error measures the accuracy of one's predictions. Standard deviation is the difference between the results of one's experiment as compared with other results within that experiment. Standard deviation is used to measure the consistency of one's experiment.
If I have understood the question correctly, despite your challenging spelling, the standard deviation is the square root of the average of the squared deviations while the mean absolute deviation is the average of the deviation. One consequence of this difference is that a large deviation affects the standard deviation more than it affects the mean absolute deviation.
difference standard deviation of portfolio
the sample standard deviation
z-score or standard score... tells you how many standard deviations away from the mean a particular number is in relations to all numbers in a population (or sample)
The standard error is the standard deviation divided by the square root of the sample size.
yes
we calculate standard deviation to find the avg of the difference of all values from mean.,
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.
* * *
The standard deviation associated with a statistic and its sampling distribution.
The mean is the average value and the standard deviation is the variation from the mean value.
σ (sigma)
If repeated samples are taken from a population, then they will not have the same mean each time. The mean itself will have some distribution. This will have the same mean as the population mean and the standard deviation of this statistic is the standard deviation of the mean.