2020
DOI: 10.12700/aph.17.5.2020.5.8
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Statistical Analysis of Machinery Variance by Python

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Cited by 4 publications
(2 citation statements)
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“…The resulting Procrustes aligned landmark coordinate data of the extant data were exported and statistically processed using Python 3.6 (see Appendix S1). The libraries and packages used for data analysis were numpy, pandas, scipy, sklearn and stats models to generate basic statistics, the principal components analyses (Pedregosa et al 2011) and sum of variances, the last of which was calculated using the three principal components scores implying the full morphospace (Ostrowski & Menyhárt 2020;Schaeffer et al 2020). Furthermore, matplotlib, mpl_toolkits and seaborn provided data visualization.…”
Section: Geometric Morphometrics and Statistical Analysismentioning
confidence: 99%
“…The resulting Procrustes aligned landmark coordinate data of the extant data were exported and statistically processed using Python 3.6 (see Appendix S1). The libraries and packages used for data analysis were numpy, pandas, scipy, sklearn and stats models to generate basic statistics, the principal components analyses (Pedregosa et al 2011) and sum of variances, the last of which was calculated using the three principal components scores implying the full morphospace (Ostrowski & Menyhárt 2020;Schaeffer et al 2020). Furthermore, matplotlib, mpl_toolkits and seaborn provided data visualization.…”
Section: Geometric Morphometrics and Statistical Analysismentioning
confidence: 99%
“…The Anderson-Darling (AD) method is used for normality testing based on a hypothesis testing with the null hypothesis stating that the data are normal and the alternate hypothesis stating that the data are not normal. Normality also can be tested by quantile-quantile plot (QQ plot) [21].…”
Section: Experimental Designmentioning
confidence: 99%