000			02112nam a22003013a 4500
001			UPMIN-00005017250
003			UPMIN
005			20230210171748.0
008			230210b |||||||| |||| 00| 0 eng d
040			_aDLC _cUPMin _dupmin
041			_aeng
090		0	_aLG993.5 2010 _bA64 T47
100			_aTeraza, Niomi T. _92387
245			_aProcrustes analysis of vocabulary flow graphs / _cNiomi T. Teraza
260			_c2010
300			_a140 leaves
502			_aThesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2010
520	3		_aThis study was conducted to determine the optional scan length in the vocabulary flor graphs. This was done through the comparison of the vocabulary flow graphs using different scan lengths though Procrustes Analysis in three textual data. Four scan lengths were used, namely: 100, 300, 500 and 1000. Using Procrustes Analysis, the vocabulary flow graphs formed from each scan lengths in each textual data were compared. Dissimilarity measures were obtained from the comparison of different scan lengths of the vocabulary flow graphs. Procrustes Statistic followed in order to test if the obtained dissimilarity measures were significant in each of the three-textual data. The end result is that all the dissimilarity measures from the comparison of scan lengths were all significant. This study had an implication in Guillermo?s translation analysis (2009) wherein he had only chosen scan length 300 as the optimal scan length among the four scan lengths. But based on the results of this study, it is still reasonable to believe that Guillermo had chosen scan length from 100, 300, 500 and 1000 were optimal values of scan lengths through the test for significance of the obtained dissimilarity measures in Procrustes statistics.
650	1	7	_aDissimilarity measure _92388
650	1	7	_aProcrustes analysis _91925
650	1	7	_aScan length _92389
650	1	7	_aTextual analysis _92390
650	1	7	_aVocabulary flow graphs _92391
658			_aUndergraduate Thesis _cAMAT200, _2BSAM
905			_aUP
905			_aFi
942			_2lcc _cTHESIS
999			_c2487 _d2487