Merits
and Demerits of Arithmetic Mean
Merits
of Arithmetic Mean:
- It is rigidly defined.
- It is easy to calculate and simple to follow.
- It is based on all the observations.
- It is determined for almost every kind of data.
- It is finite and not indefinite.
- It is readily put to algebraic treatment.
- It is least affected by fluctuations of sampling.
Demerits
of Arithmetic Mean:
- The arithmetic mean is highly affected by extreme values.
- It cannot average the ratios and percentages properly.
- It is not an appropriate average for highly skewed distributions.
- It cannot be computed accurately if any item is missing.
- The mean sometimes does not coincide with any of the observed value.
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Merits and Demerits of Geometric Mean
Merits
of Geometric Mean:
- It is rigidly defined and its value is a precise figure.
- It is based on all observations.
- It is capable of further algebraic treatment.
- It is not much affected by fluctuation of sampling.
- It is not affected by extreme values.
Demerits
of Geometric Mean:
- It cannot be calculated if any of the observation is zero or negative.
- Its calculation is rather difficult.
- It is not easy to understand.
- It may not coincide with any of the abservations.
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Merits and
Demerits of Harmonic Mean
Merits
of Harmonic Mean:
- It is based on all observations.
- It not much affected by the fluctuation of sampling.
- It is capable of algebraic treatment.
- It is an appropriate average for averaging ratios and rates.
- It does not give much weight to the large items
Demerits
of Harmonic Mean:
- Its calculation is difficult.
- It gives high weight-age to the small items.
- It cannot be calculated if any one of the items is zero.
- It is usually a value which does not exist in the given data.
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Merits and Demerits of Median
Merits
of Median :
·
It
is easy to compute and understand.
·
It is well defined an ideal average should be.
·
It can also be computed in case of frequency
distribution with open ended classes.
·
It is not affected by extreme values and also
interdependent of range or dispersion of the data.
·
It can be determined graphically.
·
It is proper average for qualitative data
where items are not measured but are scored.
Demerits of Median :
·
For
computing median data needs to be arranged in ascending or descending order.
·
It is not based on all the observations of the
data.
·
It
can not be given further algebraic treatment.
·
It
is affected by fluctuation of sampling.
·
It is not accurate when the data is not large.
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Merits
and Demerits of Mode
Merits
of Mode:
- It is easy to understand and simple to calculate.
- It is not affected by extreme large or small values.
- It can be located only by inspection in ungrouped data and discrete frequency distribution.
- It can be useful for qualitative data.
- It can be computed in open-end frequency table.
- It can be located graphically.
Demerits
of Mode:
- It is not well defined.
- It is not based on all the values.
- It is stable for large values and it will not be well defined if the data consists of small number of values.
- It is not capable of further mathematical treatment.
- Sometimes, the data having one or more than one mode and sometimes the data having no mode at all.
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