The word measure is a method to measure or ascertain certain values. Thus ‘measures of dispersion’ are the different possible methods to measure the dispersion or deviation of the various values from a series.
The variation may be measured in various numerical measures that are discussed in our Measures of Dispersion assignment help online as follows:
Range: It is a simple method to measure dispersion and it states the difference between the biggest and the smallest item in a distribution.
Range= max-min
Quartile Deviation: It is called the Semi-Inter-Quartile Range. The first quartile is Q, the middle one is Q1. The median is the second quartile or Q2. The number that connects the median and the largest number is Q3. It is calculated by:
Q=1/2 X (Q3-Q1)
Mean Deviation: It is the arithmetic mean of the deviations of observations from a mean or median.
Standard Deviation: It is the square root of an arithmetic average of the square of deviations that is measured from a Mean.
What are the Objectives to Measure Dispersion?
The objectives are discussed in our top assignment help on Measures of Dispersion as follows:
Comparative study: Measures of dispersion provide a single value that indicates the degree of uniformity or consistency of distribution. The single value can help to make comparisons of different distributions. If the value of dispersion is smaller, higher is the uniformity or consistency and vice-versa.
Reliability: A small dispersion value means low variations between average and observations. This means that an average can be reliable and a good one for observation. A higher dispersion value indicates higher deviation among the observations.
Control the variability: The measures of dispersion offer you data of variability from various angles. This knowledge may be helpful to control the variation. It is useful in financial analysis of the medical and business. The measures of dispersion might be highly useful.
Further statistical analysis: Measures of dispersion offer the basis for statistical analysis such as computation regression, correlation, the test of hypothesis, and others.