1. Standard deviation is not a measure of variance: it is the square root of the variance.
2. The answer depends on better than WHAT!
Because it is in same units as the original data. For example, if you have a sample of lengths, all in centimetres, the sample variance will be in units of centrimetres2 which might be more difficult to interpret but the sample standard deviation with be in units of centimetres, which would be relatively easy to intepret with reference to the data.
Standard deviation is generally considered better than range for measuring dispersion because it takes into account all data points in a dataset, rather than just the extremes. This allows standard deviation to provide a more comprehensive understanding of how data points vary around the mean. Additionally, standard deviation is less affected by outliers, making it a more robust measure of variability in most datasets. In contrast, range can be misleading as it only reflects the difference between the highest and lowest values.
You most certainly can. The standard deviation, however, has better statistical properties.
You subtract one from the number of observations in the denominator when calculating the sample standard deviation, as opposed to the population standard deviation. This adjustment, known as Bessel's correction, accounts for the fact that a sample is only an estimate of the population and helps to provide an unbiased estimate of the population standard deviation. By using ( n-1 ) instead of ( n ), the variability is better represented.
deviation 15 is better
Better for what? Standard deviation is used for some calculatoins, variance for others.
Because it is in same units as the original data. For example, if you have a sample of lengths, all in centimetres, the sample variance will be in units of centrimetres2 which might be more difficult to interpret but the sample standard deviation with be in units of centimetres, which would be relatively easy to intepret with reference to the data.
The standard deviation is better since it takes account of all the information in the data set. However, the range is quick and easy to compute.
When you don't have the population standard deviation, but do have the sample standard deviation. The Z score will be better to do as long as it is possible to do it.
The Standard deviation is an absolute measure of risk while the coefficent of variation is a relative measure. The coefficent is more useful when using it in terms of more than one investment. The reason being that they have different returns on average which means the standard deviation may understate the actual risk or overstate depending.
Standard deviation is generally considered better than range for measuring dispersion because it takes into account all data points in a dataset, rather than just the extremes. This allows standard deviation to provide a more comprehensive understanding of how data points vary around the mean. Additionally, standard deviation is less affected by outliers, making it a more robust measure of variability in most datasets. In contrast, range can be misleading as it only reflects the difference between the highest and lowest values.
score of 92
What is mean deviation and why is quartile deviation better than mean deviation?
You most certainly can. The standard deviation, however, has better statistical properties.
You subtract one from the number of observations in the denominator when calculating the sample standard deviation, as opposed to the population standard deviation. This adjustment, known as Bessel's correction, accounts for the fact that a sample is only an estimate of the population and helps to provide an unbiased estimate of the population standard deviation. By using ( n-1 ) instead of ( n ), the variability is better represented.
deviation 15 is better
to calculate the standard deviation you must put each number in order from the least to the gr east then you must find your mean after you find your mean you must subtract your mean from each of the data set numbers once you finishsubtracting the data set numbers you add them up and divide by the amount of numbers there are and you have found the standard deviation.