The word correlation is used in everyday life to indicate some form of association. We can say that we noticed a connection between the day and night. However, in terms of statistics we use the relationship to indicate the relationship between the two volume variables. We also assume that the relationship is linear, with a variable increasing or decreasing a fixed value for a unit that increases or falls on the other. Other methods often used in these events are conversion, where the best straight line is estimated to summarize the relationship.
      Correlation is a statistical tool that helps to measure and analyze the degree of relationship between two variables.
      Correlation analysis deals with the association between two or more
·         Degree and type of relationship between two or more quantities (variables) in which they wary together over a period.
      Example: Variation in the level of expenditure or saving with variation in the level of income.
·        In terms of the strength of relationship, the value of the correlation varies between +1 and -1.  A value of ± 1 indicates a perfect degree of association between the two variables. 
·         A+ve correlation
o   Exists where the high values of one variables associated with the high values of other variable.
o   The correlation is said to be positive correlation if the values of two variables changing with same direction
§  Ex. Pub. Exp. & sales, Height & weight.
·         A-ve correlation
o   Means association of high values of one with low values of the other.
o   The correlation is said to be negative correlation when the values of  variables change with opposite direction
·         Correlation can vary from +1 to  -1
·         Values close to +1 indicate a high degree of positive correlation.
·         Values close to -1 indicates a high degree of negative correlation.
·         Values close to 0 indicates poor correlation of either kind or 0.
·        0 indicates no correlation at all.