Standard deviation can be greater than the mean.
In general, a mean can be greater or less than the standard deviation.
It does not indicate anything if the mean is greater than the standard deviation.
Better for what? Standard deviation is used for some calculatoins, variance for others.
Quartiles in statistics are three values such that the lower quartile, second quartile (better known as the median) and upper quartile divide up the set of observations into four subsets with equal numbers in each subset.a quarter of the observations are smaller than the lower quartile,a quarter of the observations are between the lower quartile and the median,a quarter of the observations are between the median and the upper quartile, anda quarter of the observations are greater than the upper quartile,
A negative deviation means that the observation is smaller than whatever it is that the deviation is being measured from.
No. A small standard deviation with a large mean will yield points further from the mean than a large standard deviation of a small mean. Standard deviation is best thought of as spread or dispersion.
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)
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!
In the same way that you calculate mean and median that are greater than the standard deviation!
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.
No. Mean absolute deviation is usually greater than 0. It is 0 only if all the values are exactly the same - in which case there is no point in calculating a deviation! The average deviation is always (by definition) = 0
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.
25% of the observed values are smaller than the lower quartile.
It is a value such that a quarter of the observations are smaller than it and three quarters are larger.
Standard deviation in statistics refers to how much deviation there is from the average or mean value. Sample deviation refers to the data that was collected from a smaller pool than the population.
Yes; the standard deviation is the square root of the mean, so it will always be larger.
It means that the observed value is greater than that which might be expected under the model being used. Often, it is deviation from the [arithmetic] mean.
It depends on whether it is 1 SD or 2 SD above the mean or below the mean. It also depends on which is better. Sometimes being below the mean is good (time to complete a race) whereas sometimes higher than the mean is better (score in an exam).
A negative Z-Score corresponds to a negative standard deviation, i.e. an observation that is less than the mean, when the standard deviation is normalized so that the standard deviation is zero when the mean is zero.
The value of any element in the third quartile will be greater than the value of any element in the first quartile. But both quartiles will have exactly the same number of elements in them: 250.
Because the IQR excludes values which are lower than the lower quartile as well as the values in the upper quartile.
If a set of data are ordered by size, then the lower quartile is a value such that a quarter of the data are smaller than it. The upper quartile is a value such that a quarter of the data are larger than it. Interquartile means between the quartiles.
It is one of several measures of the spread of data. It is easier to calculate than the standard deviation, which has important statistical properties.