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Measures of spread (also called measures of dispersion) tell you something about how wide the set of data is. There are several basic measures of spread used in statistics. The most common are: Quartiles. The range is the distance between the lowest and highest values in a data set.
Common examples of measures of statistical dispersion are the variance, standard deviation, and interquartile range. For instance, when the variance of data in a set is large, the data is widely scattered. On the other hand, when the variance is small, the data in the set is clustered.
Recognize, describe, and calculate the measures of the spread of data: variance, standard deviation, and range. An important characteristic of any set of data is the variation in the data. In some data sets, the data values are concentrated closely near the mean; in other data sets, the data values are more widely spread out from the mean.
7 wrz 2020 · Along with measures of central tendency, measures of variability give you descriptive statistics that summarize your data. Variability is also referred to as spread, scatter or dispersion. It is most commonly measured with the following: Range: the difference between the highest and lowest values
Discover the importance of the measure of spread in statistics and data analysis. Explore key measures like range, interquartile range, standard deviation, and variance for detecting outliers and comparing datasets.
A measure of spread, sometimes also called a measure of dispersion, is used to describe the variability in a sample or population. It is usually used in conjunction with a measure of central tendency , such as the mean or median, to provide an overall description of a set of data.
Some rough measures of spread we have already discussed are the range and IQR. The most common measure of spread is the standard deviation. Similar to measures of center, the shape of the distribution and the presence of extreme values can dictate what measure of spread is most appropriate to describe the distribution.