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The data might be employed in a multivariate analysis as a result of this strategy. In this
particular instance, the data that was judged inconsistent (data that was thought to have been
tagged randomly) was excluded from inclusion in the SPSS 18.0 software package. The data
from the research was double-checked for inaccuracies, and any necessary revisions were made
as a result. Furthermore, the data collection did not include any missing data at a rate larger
than 5 percent in terms of either the person or the object. A total of 304 students in the study
sample provided research data, which was used to calculate z scores for univariate outliers and
Mahalanobis distances for multivariate outliers, among other things (Huck, 2012; Kline, 2011).
The range of Z-scores is reported to be between 3 and 6 on the scale. A total of 12 students had
their data collected, however it was not included in the data set as a result of the outliers in the
sub-factors being investigated. On this data set, there were no more outliers since the z scores
for the remaining 292 students, as well as the values in the Mahalanobis chart, were all within
acceptable boundaries. Following the assessment of the data set, the assumptions of normality,
linearity, and multicollinearity, which are all assumptions of multivariate analysis, were checked
(Hutcheson & Sofroniou, 1999; Kline, 2011; Tabachnick & Fidell, 2007).

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The data might be employed in a multivariate analysis as a result of this strategy. In this particular instance, the data that was judged inconsistent (data that was thought to have been tagged randomly) was excluded from inclusion in the SPSS 18.0 software package. The data from the research was do ...
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