Bivariate Correlation:A correlation, or Bivariate correlation,
measures the relationship between two variables. The correlation
measures the strength of the relationship. It is alternatively
known as zero order correlation.The strength of a correlation
ranges from the absolute value from 0 to 1; the closer the
correlation is to 1, the stronger the relationship, the closer the
correlation is to 0, the weaker the relationship. The direction can
be positive or negative.Here, in the analysis of Bivariate
correlation of One Bank Limited we have one dependent variable that
is Profit before tax and three independent variable those are Total
operating income, total operating expenses and provisions.The
bivariate correlation matrix found by using SPSS software is shown
in bellow:
Here we see that, there is a significant relationship between
the Total operating income and Total operating expenses in 1% level
of significance, as the coefficient is .996 which is the closest to
1. And we know that coefficients closest to 1 has the most
strongest relationship. In 1% level of significance, the
relationship between Total operating income and profit before tax
is also significant. It is .976 and the p-value is .004.Using the
5% level of significance, there is a strong relationship between
total operating expenses and profit before tax which is .956 and
the p-value is .011.Now here is a graph of scatter plot showing the
relationship between the two varriable: Total operating income and
total operating expenses.
here we see that, all the data are lying closely to the
regression line, this also give the prove of the strongest
relationship of the data of the two variable: total operating
income and total operating expenses. It is based on the 5% level of
significance. But when we wil use 5% level of significance, the
strongest relationship will lie between the total operating
expenses and profit before tax. The scatter diagram is shown
bellow:
Partial correlation:Using the SPSS software, the partial
correlation matrix is shown below:
Here, in controling for the profit before tax there is a
significatn relationship between Total operating income and the
provision which is .996 and the p-value is .004. The relationship
of total operating income with total operating expenses is also
significant.The scatter-plot showing the data of the two
variableare stated bellow:
The graph shows that almost evry data are lying closest to the
regression line, though there is variations.
Now in comparing the partial correlation and the bivaritae
correlation, we see that there are some changes in the correlation
matrix. The comparative correaltion matrix is stated bellow:
In the above correlation matrix there are two parts. The upper
part is the bivariate (zero-order) correaltion and the lower half
is the partial correlation where all the variables are controlling
for profit before tax.In the Bivariate correlation matrix, the
relationship between Total operating income and total operating
expenses is .996 but in the partial correlation matrix when the two
variable are controlling for profit before tax, there coefficient
is .993. It slightly decreases. That means the relationship between
the two variable are not significantly controlled by profit before
tax. But for the Total operating income and provision, the
correlation is .655 in bivairate correlation matrix but it become
.996 when they are conrolled by the profit before tax. There
occures a significant changes in the correlations between the
variabls when they come under the controll of the variable profit
before tax. So we can conclude that, the realtionship between the
Total operating income and provision are significantly controlled
by profit before tax
