Page 181 - DCOM203_DMGT204_QUANTITATIVE_TECHNIQUES_I

Quantitative Techniques – I

Notes
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Caution If the data are not uniformly spread in the relevant quadrants the value of r may
give a misleading interpretation of the degree of relationship between the two variables.
For example, if there are some values having concentration around a point in first quadrant
and there is similar type of concentration in third quadrant, the value of r will be very
high although there may be no linear relation between the variables.

Did u know? The coefficient of correlation lies between –1 and + 1.

Self Assessment

Fill in the blanks:
1. Distributions relating to a single characteristics are known as ..........................

2. When various units under consideration are observed simultaneously, with regard to two
characteristics, we get a ...............................
3. Study of ‘Correlation’ is meant to determine whether there exists some sort of
.................................. between the variables.
4. ................................. is the degree of association between two or more variables.
5. Correlation is an analysis of .................................. between two or more variables.

6. Correlation analysis attempts to determine the .................................. between variables.
7. .................................... is a numerical measure of the degree of association between two or
more variables.

8. A correlation coefficient calculated from the data on quantity demanded and corresponding
price of tea would only reveal that the degree of association between them is very ..................
9. The coefficient of correlation lies between ............................ and ............................

10. A .................................of the data helps in having a visual idea about the nature of association
between two variables.

8.2 Spearman’s Rank Correlation

This is a crude method of computing correlation between two characteristics. In this method,
various items are assigned ranks according to the two characteristics and a correlation is computed
between these ranks. This method is often used in the following circumstances:

1. When the quantitative measurements of the characteristics are not possible, e.g., the results
of a beauty contest where various individuals can only be ranked.
2. Even when the characteristics is measurable, it is desirable to avoid such measurements
due to shortage of time, money, complexities of calculations due to large data, etc.
3. When the given data consist of some extreme observations, the value of Karl Pearson’s
coefficient is likely to be unduly affected. In such a situation the computation of the rank
correlation is preferred because it will give less importance to the extreme observations.
4. It is used as a measure of the degree of association in situations where the nature of
population, from which data are collected, is not known.

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