MBA Thesis Daniella Griffith - Kranenberg.pdf - FHR Lim A Po ...

4.4 CorrelationCorrelation determines whether and how strong pairs of variables are related. The correlationanalysis can lead to greater understanding of your data. To know whether there is acorrelation between the variables and what the level is of the linear relationship between thevariables, the Pearson R correlation coefficient was examined. This coefficient indicates thedirection and the strength of a linear relationship between two variables. The Pearson’scorrelation coefficient (r) can vary from -1 to +1. The larger the value, the stronger therelationship. A coefficient of +1 indicates a perfect positive relationship and a coefficient of -1indicates a perfect negative relationship. 0 indicates that there is no linear relationshipbetween the variables (Field, 2009).The values for interpretation according to statistics are as follows (Pallant, 2007; Cohen,1988): Rho = .10 to .29 or -.10 to -.29 (small effect) Rho = .30 to .49 or -.30 to -.49 (medium effect) Rho = .50 to 1.0 or -.50 to -1.0 (large effect)To test the hypotheses the p-value was computed. The p-value measures the support (or lackthereof) given by the sample for the null hypothesis. Accepting or rejecting the nullhypothesis relies on the p-value, whether it is smaller than or equal to the significance level.In this case the level of significance is .05. In the following table the correlation values arepresented.34