Merits and Demerits of Mean Deviation in Business Cycle

Mean deviation is a measure that removes several shortcomings of other measures i.e. it does not ignore extreme terms or values which play a significant role in average or Mean.

According to some Economists, Mean Deviation is very useful for the forecasting of Business Cycles. Its merits and demerits can be discussed as below.

A. Merits or Uses:

1. As in case of X, every term is taken in account hence, it is certainly a better measure than other measures of dispersion i.e. Range, Percentile Range or Quartile Range.

2. Mean deviation is extensively used in other fields such as Economics, Business, Commerce or any other field of such type,

3. It has least sampling fluctuations as compared to Range, Percentile Range and Quartile Deviation.

4. When comparison is needed this is perhaps the best measure between two or more series.

5. This calculation has its base upon measurement than an estimate.

6. Mean Deviation is rigidly defined] one of the main focus point of any measure used for statistical Analysis.

7. If we calculate it from median it is less affected by extreme terms.

8. As it is based on the deviations about an average, it gives us better measure for comparison.

B. Demerits or Limitations or Drawbacks:

1. If average is in fractions, it is difficult to compute M.D.

2. Main property is absent, It is not capable of further Algebraic Treatment.

3. Not so easy to calculate to calculate X, M or Z first and then to go for other measures.

4. If it is calculated from Z it is not much reliable as Mode (Z) is not the true representative of the series.

5. M.D. and its coefficients taken from X, M and Z often differ.

6. As ± signs are ignored which is not possible mathematically. Algebraically we have to proceed for Standard Deviation; or another measure of dispersion.

7. As for mean, open end series cannot be taken for the true result.

8. If Range increases in case the sample increases, Average deviation also increases but not in the same ratio.

9. For Sociological studies, it is almost not used.