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The main objective for conducting this study is to gauge the factors responsible for motivating the students to perform in quantitative subjects (Statistics and Research Methods).
In the second stage, across subject analyses were conducted and the distribution of the individual subjects' statistics were tested for significance.
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That is why it is essential to subject statistics to a reality check.
The resulting data were fed into voxel-wise cross-subject statistics.
Each subject's aligned FA data were then projected onto this skeleton, and the resulting data were fed into voxelwise cross-subject statistics for all voxels with FA ≥ 0.30 to exclude peripheral tracts with significant inter-subject variability.
In the group analysis, across-subject statistics were calculated using a hierarchical random effects model [65] allowing for generalization of the results to the population level.
TBSS projects all subjects' FA data onto a mean FA tract skeleton, before applying voxelwise cross-subject statistics.
Each subject's aligned FA data was then projected onto this skeleton, manually inspected to confirm accurate registration, and the resulting data fed into voxelwise cross-subject statistics.
TBSS permits voxel-wise correlations by non-linearly projecting all subjects' DTI data (MD or FA) onto a mean tract skeleton before applying voxel-wise cross-subject statistics.
Each subject's aligned FA data was then projected onto this skeleton and the resulting data fed into voxelwise cross-subject statistics.
Furthermore, each subject's aligned AD and RD data were projected onto the mean FA skeleton and the resulting data fed also into voxelwise cross-subject statistics.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com