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Types of Correlation
                 There are four types of correlations which are:




                                         r=+1                                            r=–1







                                                         Positive                           Negative
                                                       Correlation                         Correlation
                                   a.                                 b.
                                                   No Correlation             Correlation is not linear
                                       r=0










                                   c.                                 d.


                 •  Positive Correlation: Positive correlation is the relationship between two variables, in which both variables have a
                    linear relationship. As one variable increases/decreases, the second variable too increases/decreases. For example,
                    when fuel prices increase, prices of airline tickets also increase.
                 •  Negative Correlation: Negative correlation is the relationship between two variables, where one variable increases
                    as the second variable decreases, and vice versa. For example, more exercising leads to a decrease in body weight.
                 •  No Correlation: No correlation means that there is no relationship between two variables. If the value of a variable is
                    changed, another variable is not affected. For example, shirt size and monthly expense, body weight and intelligence, etc.
                 •  Non-linear Correlation: A non-linear correlation is a correlation in which all the points of a scatter plot are tend to
                    lie near a smooth curve.


                        Pearson's r—Correlation Coefficient

                 The degree of association is measured by a correlation coefficient, represented by r. It is also called Pearson's correlation
                 coefficient and measures linear association between two variables. If a curved line is needed to state the relationship,
                 more complicated measures of correlation should be used.
                 The correlation coefficient is measured on a scale that varies from + 1 to – 1.

                 •  1 is a perfect positive correlation.
                 •  0 is no correlation (the values don't seem linked at all).
                 •  –1 is a perfect negative correlation.
                 Pearson’s Coefficient, r, is denoted by:
                           NΣxy–(Σx)(Σy)
                 r =
                                          2
                          2
                                2
                                      2
                       [NΣx  – (Σx) ][NΣy  (Σy) ]
                 Where  N  represents  the  number  of  samples.  Following  are  the  guidelines  given  for  interpreting  the  Pearson’s
                 Coefficient ‘r’:
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