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Design+ Importance of material selection

3.3. Relationships between demographic variables data was 141, the Kolmogorov–Smirnov test results were
and material selection criteria taken as basis. In the Kolmogorov–Smirnov test, a P > 0.05
The main purpose of the study is to determine the indicates normal distribution, while a P < 0.05 indicates
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importance levels of material selection criteria and non-normal distribution. The results of the Kolmogorov–
sustainability criteria. For this, it is first necessary to reveal Smirnov test are displayed in Table 5. This indicates that
whether the participants’ opinions differ according to their the sustainability criteria data exhibits a non-normal
demographic characteristics. A normality test was carried distribution, whereas the material selection criteria data
out since the tests to be used were chosen based on whether exhibits a normal distribution. According to these results,
the data were normally distributed. it would be appropriate to proceed with parametric tests
for the normally distributed material selection criteria data
3.3.1. Normality test and nonparametric tests for the non-normally distributed
sustainability criteria data.
Several techniques can be used to determine whether the
data are normally distributed. Using one of these methods, 3.3.2. Inferential analysis results
we determined the statistics value or standard error value
for skewness and kurtosis of the data, as presented in The goal of inferential statistics is to derive analytical
Table 4. Skewness is a metric for symmetry. If a data set or expressions for hypothesis testing or prediction on the
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distribution appears the same on the left and right of the nature of the statistical main mass. Tests that compare
center point, it is said to be symmetric. Kurtosis quantifies the means of two or more groups to ascertain whether the
how heavy-tailed or light-tailed the data are in comparison difference is random or statistically significant are known
to a normal distribution. Mayers states that a threshold as inferential analysis tests. To see whether the opinions
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value of ±3.29 should be used for samples larger than 100. differed according to demographic characteristics, the
Accordingly, the material selection criteria data have a t-test and ANOVA were used for the material selection
normal distribution (0.54; −2.20), whereas the sustainability criteria, whereas the Kruskal–Wallis and Mann–Whitney
criteria data have a non-normal distribution (4.13; 2.12). U tests were utilized for the sustainability criteria.
Another method is to conduct the Shapiro–Wilk test 3.3.3. Test results according to gender of participants
for small samples and the Kolmogorov–Smirnov test In this section, the analysis focuses on investigating
for large samples. Kolmogorov–Smirnov is used to test whether there is a significant difference in perspectives
whether the distribution of random numbers generated among participants according to their gender. Figure 3
by any method conforms to a uniform distribution within shows the means of material selection criteria and
the desired confidence intervals. Since the number of sustainability criteria according to gender. Very slight
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variations exist between the means of both groups in terms
Table 3. Descriptive statistics and the scales’ reliability values of both material selection criteria and sustainability criteria

Variable n Number Mean Min. Max. Cronbach’s (3.9558 – 3.9864 and 3.8668 – 3.8145, respectively).
of items alpha For the material selection criteria, an independent sample
Material selection 141 11 3.970 3.142 4.716 0.71 t-test, which is one of the parametric tests, was performed.
criteria The independent sample t-test analyzes the means of two
Sustainability 141 7 3.842 3.035 4.504 0.77 independent groups to ascertain whether there is statistical
criteria evidence that the means of the groups are significantly
different. In this test, if the P-value found in Levene’s test
Table 4. Scales’ kurtosis and skewness values exceeds 0.05, there is no difference between the groups. In this
case, the values in the first row are taken into consideration.
Statistic Standard error Statistic/Standard error Accordingly, the P-value is 0.733, and there is no significant
Material mean difference between genders (Table 6). Sustainability criteria
Mean 3.9703 0.04456 were analyzed with the non-parametric Mann–Whitney U
Skewness 0.110 0.204 0.54 test. This test compares two sample means and tests whether
Kurtosis −0.896 0.406 −2.20
Table 5. Kolmogorov–Smirnov test results of the scales
Sustain mean
Mean 3.8419 0.06353 Statistic df Sig.
Skewness −0.844 0.204 4.13 Material mean 0.060 141 0.200
Kurtosis 0.859 0.406 2.12 Sustain mean 0.111 141 0.000

Volume 2 Issue 1 (2025) 6 doi: 10.36922/dp.4491