## Monday, 29 August 2011

### Think Innovatively, not Wildly !!

Every subject or study has its applications. This subject which I thought will be more about using the software is in reality not. Its applications are very important as this helps us to apply our minds and make strategic decisions. As Sir has rightly said thinking is important and using it in the right direction is the key.
I was very confused as on which topic I should write but then I thought let’s write on Pearson’s Co-efficient.

What exactly is this??? In a layman terms it’s a relationship between two variables. For example: Twins can second guess each other..!!!!

It is a type of correlation coefficient that represents the relationship between two variables that are measured on the same interval or ratio scale. The value of the correlation (i.e., correlation coefficient) does not depend on the specific measurement units used; for example, the correlation between height and weight will be identical regardless of whether inches and pounds, or centimetres and kilograms are used as measurement units.

Numerically, the Pearson coefficient is represented the same way as a correlation coefficient that is used in linear regression; ranging from -1 to +1. A value of +1 is the result of a perfect positive relationship between two or more variables. Conversely, a value of -1 represents a perfect negative relationship. It has been shown that the Pearson coefficient can be deceptively small when it is used with a non-linear equation.

For example, in the stock market, if we want to measure how two commodities are related to each other, Pearson r correlation is used to measure the degree of relationship between the two commodities.

Bottom Line:

Pearson's Correlation Coefficient:

Tells us if there is linear relationship between two variables

Tells us how good the relationship is by seeing if r is close to 1 or -1 or r2 is close to 1.0.

Tells us if the relationship is positive or negative by whether r is positive or negative.

It gives an equation for a straight line so that we can predict one score from another.

Group Name: Finance 2

Author: Rishika Agarwal