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The Tenth International Arab Conference on Quality Assurance in Higher Education ﻲﻟﺎﻌﻟا ﻢﯿﻠﻌﺘﻟا ةدﻮﺟ نﺎﻤﻀﻟ ﺮﺷﺎﻌﻟا ﻲﻟوﺪﻟا ﻲﺑﺮﻌﻟا ﺮﻤﺗﺆﻤﻟا

Table 2. Shapiro–Wilk test of Normality.
a
Kolmogorov-Smirnov Shapiro-Wilk

Statistic df Sig. Statistic df Sig.
improvement .151 38 .028 .957 38 .152

By Shapiro–Wilk test showed in Table 2, we find p-value=0.152 which is greater than α=0.05, then the null
hypothesis that the data came from a normally distributed population can’t be rejected, and the data is asymptotically
normal. So we were able to use the T-Test which is a parametric test Table 3 shows.

Table 3. Group Statistics, T-Test.

Std. Std.Error
Method N Mean
Deviation Mean
Agile 18 8.94 2.461 .580
improvement
Waterfall 20 5.50 3.502 .783

According to Levene’s Test for Equality of Variances showed in Table 4, we find a homogeneity of variance between
the two samples since sig. = 0.130. Then we read our values from the first row. Since p-value = 0.001 which is less
than α=0.05, we reject the related null hypothesis, which means at level of significant α=0.05 the data give us a
sufficient evidence to conclude that there is a significant difference between the means of the experimental and
control groups, which are respectively 8.94 and 5.50.

Table 4. Independent Samples Test, T-Test.
Levene's Test for
Equality of Variances t-test for Equality of Means
95% Confidence
Mean Std. Error Interval of the
F Sig. t df Sig. (2-tailed)
Difference Difference Difference
Lower Upper
Equal variances 2.404 .130 3.471 36 .001 3.444 .992 1.432 5.457
Improv assumed
ement Equal variances 3.535 34.097 .001 3.444 .974 1.464 5.425
not assumed

At projects discussion, Agile groups showed a better understanding of the materials. In spite of control groups who
have cut corners to finish their products with obvious negligence of methodology principles. That is strongly support
our results in this most important part of the research.

1.10 Time to Market:
For the methodology factor, completeness indicated the time needed, in term of features completed, divided by
features required. The results are stated in Table 5.

Table 5. Projects Completeness.
No. feat/ No. feat/
Project Context Team Team
req. feat req. feat
Dental Clinic Systems A1 26/28 24/28 W1
Medical Laboratory Systems A2 36/37 30/34 W2
Cars Insurance Systems A3 31/36 27/36 W3
Child Care Center Systems A4 29/29 26/29 W4

The feature is formed in user stories and tasks. It considered completed, if its main user stories are done (coded,
reviewed and integrated). The data in Table 5, shows the results for both methods, and it let us reject the null
hypothesis.

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