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Unformatted text preview: n height of father and son, yield and
rainfall, wage and price index, share and debentures etc.
Correlation is statistical Analysis which measures and
analyses the degree or extent to which the two variables fluctuate
with reference to each other. The word relationship is important. It
indicates that there is some connection between the variables. It
measures the closeness of the relationship. Correlation does not
indicate cause and effect relationship. Price and supply, income
and expenditure are correlated.
1. Correlation Analysis attempts to determine the degree of
relationship between variables- Ya-Kun-Chou.
2. Correlation is an analysis of the covariation between two
or more variables.- A.M.Tuttle.
Correlation expresses the inter-dependence of two sets of
variables upon each other. One variable may be called as (subject)
191 independent and the other relative variable (dependent). Relative
variable is measured in terms of subject.
Uses of correlation:
1. It is used in physical and social sciences.
2. It is useful for economists to study the relationship between
variables like price, quantity etc. Businessmen estimates
costs, sales, price etc. using correlation.
3. It is helpful in measuring the degree of relationship
between the variables like income and expenditure, price
and supply, supply and demand etc.
4. Sampling error can be calculated.
5. It is the basis for the concept of regression.
It is the simplest method of studying the relationship
between two variables diagrammatically. One variable is
represented along the horizontal axis and the second variable along
the vertical axis. For each pair of observations of two variables, we
put a dot in the plane. There are as many dots in the plane as the
number of paired observations of two variables. The direction of
dots shows the scatter or concentration of various points. This will
show the type of correlation.
1. If all the plotted points form a straight line from lower left hand
corner to the upper right hand corner then there is...
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- Winter '08