Along with measures of central tendency, measures of variability give you descriptive statistics for summarizing your data set. The range is calculated by subtracting the lowest value from the highest value. While a large range means high variability, a small range means low variability in a distribution.
In descriptive statistics, range is the size of the smallest interval which contains all the data and provides an indication of statistical dispersion. Since it only depends on two of the observations, it is most useful in representing the dispersion of small data sets.
In statistics, the range is the spread of your data from the lowest to the highest value in the distribution. It is a commonly used measure of variability. Along with measures of central tendency, measures of variability give you descriptive statistics for summarizing your data set.
Range is a descriptive statistics measurement that statisticians, analysts and mathematicians use to find the
difference between the highest and lowest value in a data set. The range helps you understand how varied the numbers are within a given set.The range describes the
difference between the largest and smallest data point in our data set. The bigger the range, the more the spread of data and vice versa. Range = Largest data value – smallest data valueAlong with measures of central tendency, measures of variability give you descriptive statistics for summarizing your data set. The range is calculated by
subtracting the lowest value from the highest value. While a large range means high variability, a small range means low variability in a distribution.
The range, standard deviation and variance each reflect different aspects of spread. The range gives you an idea of how far apart the most extreme response scores are. To find the range, simply subtract the lowest value from the highest value.
In descriptive statistics, range is the
size of the smallest interval which contains all the data and provides an indication of statistical dispersion. Since it only depends on two of the observations, it is most useful in representing the dispersion of small data sets.
