♥Findings

Contents

1)Scatter plot

2)Pearson's Correlation Coefficient (Pearson's r)

3)Linear Regression

1.Scatter plot

The scatter plot graph is used to test for linearity and homogenous variance of the 2 variables, these being two of the assumptions to be made before using Pearson's r

The upwards sloping nature of the fit indicates that there is a positive correlation between the 2 variables.

Thus,the scatter plot graph shows that the relationship between right arm and right leg is strong,negative one.Now that the 2 variables are shown to have a linear relationship and having the same variability.

2.Pearson's Correlation coefficient (Pearson's r)

According to the Pearson's r correlation coefficient it is moderately strong relationship between the arm and the leg blood pressure reading.The diagram indicates a correlation coefficient of 0.499,which indicates a moderately strong relationship between the blood pressure of the right arm and the right leg readings.

        As indicated from the SPSS data, Pearson's r =0.621 , which indicates a positive, moderately strong and significant relationship.

3)Liner Regression

Now that we know the 2 variables are correlated, we can use one value of one variable to predict the value of the other by deriving a linear equation from the computed data