measures of variation
The answer depends on the type of distribution for the data. It could be the modal class.
Each of these measures of central tendency has its own advantages and disadvantages. Different measures are best in different circumstances.
Yes, if there is no variation: all the data have to have the same value and that value must be non-zero.
The coefficient of variation is a method of measuring how spread out the values in a data set are relative to the mean. It is calculated as follows: Coefficient of variation = σ / μ Where: σ = standard deviation of the data set μ = average of the data set If you want to know more about it, you can visit SilverLake Consulting which will help you calculate the coefficient of variation in spss.
measures of variation
There are a number of appropriate displays to show the measures of variation for a data set. Different graphs can be used for this purpose which may include histograms, stemplots, dotplots and boxplots among others.
The answer depends on the type of distribution for the data. It could be the modal class.
You describe the shape, not of the data set, but of its density function.You describe the shape, not of the data set, but of its density function.You describe the shape, not of the data set, but of its density function.You describe the shape, not of the data set, but of its density function.
A measure of variation, also called a measure of dispersion, is a type of measurement that details how a set of data is scattered from a central or neutral point of origin. Range, variance and standard deviation are three measures of variation that are commonly used.
Each of these measures of central tendency has its own advantages and disadvantages. Different measures are best in different circumstances.
Yes, if there is no variation: all the data have to have the same value and that value must be non-zero.
The answer will depend on the set of data!
The coefficient of variation is a method of measuring how spread out the values in a data set are relative to the mean. It is calculated as follows: Coefficient of variation = σ / μ Where: σ = standard deviation of the data set μ = average of the data set If you want to know more about it, you can visit SilverLake Consulting which will help you calculate the coefficient of variation in spss.
The standard deviation is a measure of how much variation there is in a data set. It can be zero only if all the values are exactly the same - no variation.
Of course it is! If the mean of a set of data is negative, then the coefficient of variation will be negative.
There is no single number. There are several different measures of central tendency - different ones are better in different circumstances. Then there are several measures of spread or dispersion, skewness and so on. All of these are characteristics of the data and they cannot all be summarised by a single number.