Assembling The Project Compendium - Computing Technical ...

Quantitative analysis involved turning the count of answers into percentages based on the
number of people who answered that particular question and double checked against data
displayed by Surveymonkey. For the question about industry sector, any classifications
where the population was less than three percent, were incorporated under the „other‟
classification. Most data was used to create frequency distribution charts.
Likert scaling was used to calculate the relative necessity of components for different
elements of project success according to the collective responses from the survey sample.
(Refer to appendix D for details of Likert scale calculations.) There is much debate as to
whether Likert scaling can be used in such circumstances. Likert scaling was thought to be
an appropriate method based on the following assumptions. The ordinal data collected
from the Likert scores were considered to be interval and continuous in nature.
Multivariate statistical analysis techniques can be applied to the ordinal data (Carifio et al.,
2008; Clason and Dormody, 1994; Lubke et al., 2004; Pell and Pell, 2005; Wu, 2009). The
group can be compared in a meaningful way because the data is from a single homogenous
population and the questionnaire is resistant to variation across groups (Lubke et al., 2004).
The assumptions about the data have been clearly stated (Pell and Pell, 2005). The inferred
conclusions were carefully considered (Clason and Dormody, 1994). The advantage of the
Likert scores is that it allowed a single number to describe the overall opinion of the
population (Trochim, 2006).
To pictorially demonstrate the perceived necessity of components for individual elements of
success, the components were ordered according to their Likert scores and plotted onto
charts.
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