Archive | Statistics

The measures of Central Tendency and Dispersion are used to compare two or more series. But it is not the comparison that is always wanted.

The objects of Descriptive Statistics are mainly – condensation by frequency distribution, and description of the frequency distribution by suitable statistical measures.

It is the form of a curve which is derived from the cumulative percentage of the given variables. This curve was given by Dr. Max O. Lorenz a popular Economic- Statistician. He studied distribution of Wealth and Income with its help.

The idea of Standard Deviation was first presented by Karl Pearson in 1893. This measure is widely used for studying dispersion.

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.

Absolute measures of Dispersion are expressed in same units in which original data is presented but these measures cannot be used to compare the variations between the two series.

So going through the merits and demerits, we conclude that Quartile Deviation cannot be relied on blindly.

Merits and Demerits of Range…

Literally, dispersion means deviation, difference or spread of certain values from their central value. In relation to statistical seris, it means, deviations of various items of the series from its ventral value.

The use or application of a particular average depends upon the purpose of the investigation. Some of the cases of different averages are as follows:

What are the Merits and Demerits of Harmonic Mean?

What are the Merits and Demerits of Geometric mean (GM)?

What is the Empirical relation between Mean, Mode and Median?

Mode may be defined as the value that occurs most frequently in a statistical distribution. In French language ‘Mode’ means ‘Fashion’.

What are the Merits and Demerits of Median?

According to A.L. Bowley, “Statistics may rightly be called as the science of averages.” This average is also known as central value. Through statistical analysis we condense the whole data to a single value, which represents the data in true sense.