As another example, after carefully examining the distribution of income and wealth, the government can make the necessary policy measures to eliminate the disparities in the distribution of income and wealth. This enables us to pinpoint the root reasons for variance in the manufactured good and take appropriate corrective and remedial action. For instance, we use 3-sigma control limits to assess the controllability of a manufacturing process. It aids in determining how many various tasks carried out in industries deviate from the norm in terms of quality. In order to control the variation itself, the measures of variation assist us in identifying its nature and causes. 2. To minimize the data’s deviation from the central value. The data values will be further away from the central value if the dispersion is high, suggesting that the average is not accurate and therefore not very reliable. The average can be regarded as dependable in the sense that it gives a reasonably accurate estimate of the average for the related population if the dispersion is small, which indicates that the given data values are closer to the average (central value). Dispersion, as previously mentioned, provides information on the distribution of data around an average value. We can determine whether the average is representative of the data using the measures of variation. To determine whether an average is reliable. Objectives and Significance of Measures of Dispersion 1. The degree of the scatter or variation of the variables around a central value is known as dispersion or spread. The variance or dispersion of the data is the measure of how widely distributed numerical data tend to be around an average value. To determine whether the distribution is homogeneous (compact) or heterogeneous (scattered), we look at dispersion.
If we are to determine how representative the average is, a more thorough explanation of the series is required.Īs a result, extra measurements known as the measures of dispersion must be used in addition to and to support the measures of central tendency. It is hardly a complete representation of the data unless we are aware of how the different data values disperse around it. The complete story of the data is not revealed by an average. Characteristics of Ideal Measures of Dispersion.Objectives and Significance of Measures of Dispersion.
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