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Why is standard deviation a better measure of dispersion than variance?
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.
Can a standard deviation of 4.34 be correct?
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.
What do you mean when you say that the coefficient of variation has no units?
Suppose the mean of a sample is 1.72 metres, and the standard deviation of the sample is 3.44 metres. (Notice that the sample mean and the standard deviation will always have the same units.) Then the coefficient of variation will be 1.72 metres / 3.44 metres = 0.5. The units in the mean and standard deviation 'cancel out'-always.
What standard unit of measure?
It depends on what you are trying to measure. There are different standard units for different characteristics.
What is the effective range of standard deviation units on both sides of the mean?
The are effective as far as the domain of the random variable, and that domain may be infinite.
Which type of measure of dispersion is mostly used standard deviation or variance?
They are effectively the same but the standard deviation is more popular because the units of measurement are the same as those for the variable.
What are the units of measurement of standard deviation?
Standard deviation has the same unit as the data set unit.
Why is standard deviation a better measure of dispersion than variance?
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.
What is relative measure?
These measures are calculated for the comparison of dispersion in two or more than two sets of observations. These measures are free of the units in which the original data is measured. If the original data is in dollar or kilometers, we do not use these units with relative measure of dispersion. These measures are a sort of ratio and are called coefficients. Each absolute measure of dispersion can be converted into its relative measure. Thus the relative measures of dispersion are:Coefficient of Range or Coefficient of Dispersion.Coefficient of Quartile Deviation or Quartile Coefficient of Dispersion.Coefficient of Mean Deviation or Mean Deviation of Dispersion.Coefficient of Standard Deviation or Standard Coefficient of Dispersion.Coefficient of Variation (a special case of Standard Coefficient of Dispersion)
Can a standard deviation of 4.34 be correct?
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.
What are the units of dispersion?
The units of dispersion are dependent on the units of the data being measured. Common measures of dispersion include variance and standard deviation, which have square units and the same units as the data being measured, respectively. Another measure, such as the coefficient of variation, is a unitless measure of dispersion relative to the mean.
What do you mean when you say that the coefficient of variation has no units?
Suppose the mean of a sample is 1.72 metres, and the standard deviation of the sample is 3.44 metres. (Notice that the sample mean and the standard deviation will always have the same units.) Then the coefficient of variation will be 1.72 metres / 3.44 metres = 0.5. The units in the mean and standard deviation 'cancel out'-always.
Why is the standard deviation used more frequently than the variance?
The standard deviation has the same measurement units as the variable and is, therefore, more easily comprehended.
Without calculating the standard deviation why does the set 4 4 20 20 have a standard deviation of 8?
The mean is 12 and each observation is 8 units away from 12.
Why does the formula for standard deviation have a square root in it?
The formula for standard deviation has both a square (which is a power of 2) and a square-root (a power of 1/2). Both must be there to balance each other, to keep the standard deviation value's magnitude similar to (having the same units as) the sample numbers from which it's calculated. If either is removed from the formula, the resulting standard deviation value will have different units, reducing its usefulness as a meaningful statistic.
What standard unit of measure?
It depends on what you are trying to measure. There are different standard units for different characteristics.
Variance and standard deviation are one and the same thing?
No. But they are related. If a sample of size n is taken, a standard deviation can be calculated. This is usually denoted as "s" however some textbooks will use the symbol, sigma. The standard deviation of a sample is usually used to estimate the standard deviation of the population. In this case, we use n-1 in the denomimator of the equation. The variance of the sample is the square of the sample's standard deviation. In many textbooks it is denoted as s2. In denoting the standard deviation and variance of populations, the symbols sigma and sigma2 should be used. One last note. We use standard deviations in describing uncertainty as it's easier to understand. If our measurements are in days, then the standard deviation will also be in days. The variance will be in units of days2.
