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Dispersion Measures

The average alone cannot adequately describe a set of observations, unless all the observations are the same. It is necessary to describe the variability or dispersion of the observations. In two or more distributions the central value may be the same but still there can be wide disparities in the formation of distribution. Measures of dispersion help us in studying this important characteristic of a distribution.

The dispersion can be defined as:

Dispersion is the measure of the variation of the items. The degree to which numerical data tend to spread about an average value is called the variation or dispersion of the data. Dispersion or spread is the degree of the scatter or variation of the variable about a central value. The measurement of the scatteredness of the mass of figures in a series about an average is called measure of variation or disperses. It is clear from above that dispersion also known as scatter, spread or variation) measures the extent to which the items vary from some central value. Since measures of dispersion give average of the differences of various items from an average, they are also called averages of the second order.

An average is more meaningful when it is examined in the light of dispersion. For example, if the average wage of the workers of factory

Some of its main topics are:

The dispersion can be defined as:

Dispersion is the measure of the variation of the items. The degree to which numerical data tend to spread about an average value is called the variation or dispersion of the data. Dispersion or spread is the degree of the scatter or variation of the variable about a central value. The measurement of the scatteredness of the mass of figures in a series about an average is called measure of variation or disperses. It is clear from above that dispersion also known as scatter, spread or variation) measures the extent to which the items vary from some central value. Since measures of dispersion give average of the differences of various items from an average, they are also called averages of the second order.

An average is more meaningful when it is examined in the light of dispersion. For example, if the average wage of the workers of factory

**A**is**$ 3855**and that of factory**B $ 3990**, we cannot necessarily conclude that the workers of factory**B**are of better off because in factory**B**there may be much greater dispersion in the distribution of wages.Some of its main topics are:

**1.**Studying variation-methods**2.**Variation significance**3.**Mean deviation**4.**Mean deviation calculation**5.**Arithmetic mean calculation**6.**Standard deviation**7.**Standard deviation-properties**8.**Standard deviation-discrete series**9.**Standard deviation-continuous series**10.**Variation coefficient**11.**Lorenz curve**12.**Quartile deviation**13.**Tchebycheff's theorem**Services:-**Dispersion Measures Homework | Dispersion Measures Homework Help | Dispersion Measures Homework Help Services | Live Dispersion Measures Homework Help | Dispersion Measures Homework Tutors | Online Dispersion Measures Homework Help | Dispersion Measures Tutors | Online Dispersion Measures Tutors | Dispersion Measures Homework Services | Dispersion MeasuresSubmit Your Query ???

Assignment Help

Business Forecasting
Central Value Measures
Correlation Regression Analysis
Data Tabulation
Diagrammatic Graph Presentation
Dispersion Measures
Experimental Designs
F Test Variance Analysis
Index Numbers
Partial Multiple Correlation
Probability Expected Value
Sampling Designs
Skewness Moments Kurtosis
Statistical Survey
Decision Theory
Statistical Fallacies
Statistical Quality Control
Statistics What Why
Theoretical Distribution
Vital Statistics
F2 Test
Topics

Continuous Arithmetic Mean
Lorenz Curve
Continuous Mean Deviation
Mean Deviation
Quartile Deviation
Standard Deviation
Continuous Standard Deviation
Discrete Standard Deviation
Standard Deviation Properties
Studying Variation Methods
Tchebycheffs Theorem
Variation Coefficient
Variation Significance

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