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SIMPLE CORRELATION.

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Presentation on theme: "SIMPLE CORRELATION."— Presentation transcript:

1 SIMPLE CORRELATION

2 Correlation is analysis of the co-variation between 2 or more variables. -A.M Tuttle Correlation analysis attempts to determine the degree of relationship between variables. -Ya Lun Chou

3 SIGNIFICANCE OF CORRELATION
ANALYSIS :

4 1) The correlation coefficient help us in measuring the extent of relationship between 2 or more than 2 variables. 2)It is through correlation that we can predict about the future .For instance ,if there are good monsoons we can expect better supply and hence can expect fall in price of foodgrains and other products.

5 3)If the value of a variable is given, we can know the value of another variable. It is of course done with the help of regression analysis. 4)Correlation contributes to economic behaviour. It helps us in knowing the important variables on which others depend.

6 5)The techniques of ratio of variation and regression analysis depends totally on the findings of co-efficiant of correction. 6)In the field of commerce and industry the technique of correlation coefficient helps to make estimates like sales, price or costs. 7)The prediction made on the basis of correlation analysis are considered to be nearer do reality and hence reliable .

7 PROPERTIES OF KARL PERASONS COEFFICIENT :

8 1)In case correlation is present, then coefficient of correlation would lie between +1. If correlation is absent then it is denoted by zero or -< r < 1. 2)Coefficient of correlation in based on a suitable measure of variation as it takes into account all items of the variants. 3)Coefficient of correlation measures both the direction as well as degree of change.

9 4)If there is accidently correlation in that case the coefficient of correlation might lead to fallacious conclusions. It is known as non-sense or spurious correlation 5)The coefficient of correlation does not prove causation but it is simply a measure of co-variation. It is because variations in X and 7 series may be due :

10 Some common cause. Some mutual dependence Some change Some causation of the subject to be relative.

11 6)It is independent of changes of scale and origin of the variables.
7)Coefficient of correlation is geometric mean of 2 regression coefficients. 8)Coefficient of correlation is independent of the unit of measurement.

12 9)Coefficient of correlation works both ways i.e rXy=ryx
10)If the value of X and y are linearly related with each other i.e if we have the relation between x and y as y=aXb the correlation coefficient between x and y will be +1 and if the relation between x and y is as y=ax+b ,then ‘r’ will be a being a negative constant.

13 THANK YOU


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