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Unformatted text preview: nterpreted as a measure of monotonicity. That is, Spearman’s
correlation coefficient is a standardised index of the degree to which two variables
covary in a monotonic fashion. The Spearman’s correlation coefficient index can
range from –1.0 to 1.0. It will attain these maximum values when a perfect monotonic relationship is negative or positive, respectively. The rank order correlation coefficient will be zero when there is no relationship between two
variables, or when the relationship is strong but nonmonotonic. Since Spearman’s
rank correlation coefficient is equivalent to Pearson’s correlation coefficient
computed on scores, it has some of the same characteristics. For example, since
Pearson’s correlation coefficient is equal to the regression coefficient in the special
case where the variances of the two populations are equal it now follows that
Spearman’s correlation coefficient is also the linear regression coefficient for two
ranked variables. As such, it indicates the amount of “rank change” in one population
when the other increases by one rank. It can also be shown that Spearman’s rank
order correlation coefficient indicates the proportion of variation in one population
that is explained by variation in the other population. Spearman’s rank order correlation test is considered by some statisticians to be a “quick and dirty”
approximation for Pearson’s correlation coefficient. However, when data are ordinal
the Pearson’s correlation coefficient is not appropriate. In this case, Spearman’s
correlation coefficient is the most desirable index (Leach, 1979).
Where categorical data was available and there was sufficient number of data points
on a performance criterion, a Kruskal Wallis test was also used. This test is outlined
in Appendix 4. The Kruskal Wallis test is a direct generalisation of the Wilcoxon
Rank Sum test. When a significant result is obtained with the Kruskal Wallis test, all
that can be concluded is that there is some difference in location between the samples. 68 To find the location of this difference, the Wilcoxon Rank Sum test was used. This is
also outlined in Appendix 4.
Through the utilisation of these two non-parametric tools, the author was able to
produce evidence of an association between good organisational performance and the
use of decision analysis techniques in investment appraisal decision-making in the
operating companies in the U.K. upstream oil and gas industry.
This section has outlined the research methodology used to answer the three research
questions proposed in Chapter 1. The following section will assess its effectiveness
and suggest possible improvements.
4.3 EVALUATING THE EFFECTIVENESS OF THE RESEARCH METHODOLOGY
Through the utilisation of qualitative methods and statistical analysis the research
presented in this thesis has generated a robust body of data. This claim can be
justified on three counts.
First, using the academic investment decision-making and oil industry literatures, an
approach to investment decision-making has been developed that utilises the full
complement of decision analysis techniques presented in the decision theory
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This document was uploaded on 03/30/2014.
- Summer '14
- The Land