Bibliografías temáticas / Statistical (ANOVA)

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Literatura académica sobre el tema "Statistical (ANOVA)"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 1 de febrero de 2022

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Artículos de revistas sobre el tema "Statistical (ANOVA)"

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Brereton, Richard G. "ANOVA tables and statistical significance of models." Journal of Chemometrics 33, no. 3 (2018): e3019. http://dx.doi.org/10.1002/cem.3019.

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Keselman, H. J., Carl J. Huberty, Lisa M. Lix, et al. "Statistical Practices of Educational Researchers: An Analysis of their ANOVA, MANOVA, and ANCOVA Analyses." Review of Educational Research 68, no. 3 (1998): 350–86. http://dx.doi.org/10.3102/00346543068003350.

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Potvin, Patrick J., and Robert W. Schutz. "Statistical power for the two-factor repeated measures ANOVA." Behavior Research Methods, Instruments, & Computers 32, no. 2 (2000): 347–56. http://dx.doi.org/10.3758/bf03207805.

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Ping, Wen, Chen Shengduo, Wang Jiarui, and Che Wei. "ANOVA Statistical Significance Analysis of Clinicopathological Characteristics Tumor Tissue." Journal of Medical Imaging and Health Informatics 10, no. 1 (2020): 38–43. http://dx.doi.org/10.1166/jmihi.2020.2857.

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Driscoll, Wade C. "Robustness of the ANOVA and Tukey-Kramer statistical tests." Computers & Industrial Engineering 31, no. 1-2 (1996): 265–68. http://dx.doi.org/10.1016/0360-8352(96)00127-1.

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Simon, Stephen D., and James P. Lesage. "Assessing the accuracy of ANOVA calculations in statistical software." Computational Statistics & Data Analysis 8, no. 3 (1989): 325–32. http://dx.doi.org/10.1016/0167-9473(89)90048-0.

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Liu, Fang, and Laiyong Zhou. "Statistical ANOVA Analysis for Early Detection of Nasopharyngeal Carcinoma Cells." Journal of Medical Imaging and Health Informatics 10, no. 1 (2020): 139–42. http://dx.doi.org/10.1166/jmihi.2020.2869.

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Kim, Jong-Geon, Yong-Seok Choi, and Nae-Young Lee. "Unbalanced ANOVA for Testing Shape Variability in Statistical Shape Analysis." Korean Journal of Applied Statistics 23, no. 2 (2010): 317–23. http://dx.doi.org/10.5351/kjas.2010.23.2.317.

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Glenn, D. Michael. "Statistical Analysis of Root Count Data." HortScience 30, no. 4 (1995): 907A—907. http://dx.doi.org/10.21273/hortsci.30.4.907a.

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The minirhizotron approach for studying the dynamics of root systems is gaining acceptance; however, problems have arisen in the analysis of data. The purposes of this study were to determine if analysis of variance (ANOVA) was appropriate for root count data, and to evaluate transformation procedures to utilize ANOVA. In peach, apple, and strawberry root count data, the variance of treatment means was positively correlated with the mean, violating assumptions of ANOVA. A transformation based on Taylor's power law as a first approximation, followed by a trial and error approach, developed transformations that reduced the correlation of variance and mean.
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Maxwell, Scott E., Harold D. Delaney, and Jerry M. Manheimer. "Anova of Residuals and Ancova: Correcting an Illusion by Using Model Comparisons and Graphs." Journal of Educational Statistics 10, no. 3 (1985): 197–209. http://dx.doi.org/10.3102/10769986010003197.

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Analysis of covariance is often conceptualized as an analysis of variance of a single set of residual scores that are obtained by regressing the dependent variable on the covariate. Although this conceptualization of an equivalence between the two procedures may be intuitively appealing, it is mathematically incorrect. If residuals are obtained from the pooled within-groups regression coefficient ( bw), an analysis of variance on the residuals results in an inflated α-level. If the regression coefficient for the total sample combined into one group ( bT) is used, ANOVA on the residuals yields an inappropriately conservative test. In either case, analysis of variance of residuals fails to provide a correct test, because the significance test in analysis of covariance requires consideration of both bw and bT, unlike analysis of residuals. It is recommended that the significance test of treatment effects in analysis of covariance be conceptualized, not as an analysis of residuals, but as a comparison of models whose parameters are estimated by the principle of least squares. Focusing on model comparisons and their associated graphs can be used effectively here as in other cases to teach simply and correctly the logic of the statistical test.
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Tesis sobre el tema "Statistical (ANOVA)"

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An, Qian. "A Monte Carlo study of several alpha-adjustment procedures using a testing multiple hypotheses in factorial anova." Ohio : Ohio University, 2010. http://www.ohiolink.edu/etd/view.cgi?ohiou1269439475.

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Gu, Jin. "Statistical partition problem for exponential populations and statistical surveillance of cancers in Louisiana." ScholarWorks@UNO, 2014. http://scholarworks.uno.edu/td/1921.

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In this dissertation, we consider the problem of partitioning a set of k population with respect to a control population. For this problem some multistage methodologies are proposed and their properties are derived. Using the Monte Carlo simulation techniques, the small and moderate sample size performance of the proposed procedure are studied. We have also considered at statistical surveillance of various cancers in Louisiana.
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An, Qian. "A Monte Carlo Study of Several Alpha-Adjustment Procedures Used in Testing Multiple Hypotheses in Factorial Anova." Ohio University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1269439475.

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Senteney, Michael H. "A Monte Carlo Study to Determine Sample Size for Multiple Comparison Procedures in ANOVA." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou160433478343909.

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Anday, Tekie T. "Application of ANOVA for the analysis of temporal and spatial differences in the length of pelagic goby preyed on by Cape fur seals in the coasts of Namibia." Master's thesis, University of Cape Town, 2005. http://hdl.handle.net/11427/4369.

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Includes bibliographical references (leaves 62-66).<br>The Analysis of variance is a robust technique whereby the total variation present in a set of data is partitioned into two or more components (Wayne, 1999). In this thesis, ANOVA was used to uncover the differences in goby length preyed on by three different colonies of fur seals at the Namibian coast. Moreover, ANOVA was used to investigate temporal differences in lengths of goby preyed on by fur seals in each location of the seal colonies. Results of the analysis are shown in the Analysis and results section, and the findings are discussed in the discussion section. But before these two sections, there are three sections of the thesis. The first section is the general introduction that explains about the general situation and the targets of this thesis. The second section gives a general background on the ANOVA technique. The third section explains the nature of the data and gives background information on gobies.
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Mu, Zhiqiang. "Comparing the Statistical Tests for Homogeneity of Variances." Digital Commons @ East Tennessee State University, 2006. https://dc.etsu.edu/etd/2212.

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Testing the homogeneity of variances is an important problem in many applications since statistical methods of frequent use, such as ANOVA, assume equal variances for two or more groups of data. However, testing the equality of variances is a difficult problem due to the fact that many of the tests are not robust against non-normality. It is known that the kurtosis of the distribution of the source data can affect the performance of the tests for variance. We review the classical tests and their latest, more robust modifications, some other tests that have recently appeared in the literature, and use bootstrap and permutation techniques to test for equal variances. We compare the performance of these tests under different types of distributions, sample sizes and true ratios of variances of the populations. Monte-Carlo methods are used in this study to calculate empirical powers and type I errors under different settings.
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Nueda, Roldán María José. "Statistical methods for time course microarray data." Doctoral thesis, Universitat Politècnica de València, 2009. http://hdl.handle.net/10251/6061.

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La tesis aborda el análisis estadístico de series simples y múltiples de experimentos de "Time Course Microarray" (TCM). El trabajo se centra en el desarrollo, aplicación y evaluación de métodos estadísticos específicos que consideran la problemática de este tipo de datos, tanto desde el punto de vista de selección de genes como del análisis funcional. Las técnicas desarrolladas se comparan con otros métodos del estado del arte actual evaluando las diferentes metodologías en términos de eficiencia y significado biológico de los resultados. En la tesis se incluye la descripción del funcionamiento de la tecnología de "microarrays" así como una revisión crítica de los métodos estadísticos aplicados a este tipo de datos mostrando los inconvenientes que surgen al aplicar métodos generales a series temporales de "microarrays" y justificando la necesidad de desarrollar nuevas técnicas para el análisis de TCM. La primera técnica desarrollada es maSigPro ("microarray Significant Profile") que usa análisis de regresión lineal para modelar la expresión génica y lleva a cabo una estrategia en dos pasos para seleccionar los genes diferencialmente expresados. La aplicación de la técnica multivariantes ASCA (ANOVA "Simultaneous Component Analysis") a datos de TCM da como resultado el método ASCA-genes que combina la exploración multivariante de datos con un procedimiento de selección para identificación de genes con cambios relevantes. El método ASCA es también usado para crear una estrategia de filtrado de datos de gran utilidad para eliminar el alto nivel de ruido estructural de los datos de microarrays. Por último, se desarrollan métodos estadísticos para una evaluación directa e integrada de las alteraciones que pueden sufrir las funciones génicas en TCM. Para este propósito, se ha adaptado las técnicas maSigPro, ASCA y PCA incorporándoles información funcional obteniendo las metodologías maSigFun, PCA-maSigFun y ASCA-functional.<br>Nueda Roldán, MJ. (2009). Statistical methods for time course microarray data [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/6061<br>Palancia
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Frisch, Jessica Lynne. "Chromatographic and mass spectral analyses of oligosaccharides and indigo dye extracted from cotton textiles with manova and anova statistical data analyses." Orlando, Fla. : University of Central Florida, 2008. http://purl.fcla.edu/fcla/etd/CFE0002068.

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Iqbal, Sardar S. "IMPACT OF HEAT TREATMENT AND OXIDATION OF C/C COMPOSITES ON MICROSTRUCTURE AND PHYSICAL PROPERTIES." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/dissertations/430.

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Carbon-carbon (C/C) composites are notable among engineering materials in aerospace and defense industries possessing excellent specific mechanical, thermal, frictional and wear properties. C/C maintain their properties at temperatures where most of the high end alloys give in, and maintain their dimensional stability at temperatures above 2000 oC. C/C is frequently used in aircraft and automotive industries as brake materials. However, frictional performance is dependent on various parameters: microstructure, fiber type, fiber orientation distribution, fiber/matrix interfacial bond, heat treatment, and oxidation. The present study in dissertation provides an insight into the impact of heat treatment, and oxidation on microstructure, mechanical and thermal properties. The heat treatment (performed at 1800, 2100, 2400 oC in argon) of two-directional (2-D) pitch-fiber with charred resin carbon matrix, and three-directional (3-D) PAN-fiber with CVI carbon matrix influenced microstructure, mechanical and thermal properties. Microstructure characterized by polarized light microscopy (PLM), XRD, and Raman spectroscopy changed with increasing heat treatment temperature. The RL microstructure of 3-D C/C progressively highly organized, whereas ISO microstructure of 2-D C/C's charred resin hardly organized into an ordered structure as evident from Raman spectroscopy and Raman profiling of polished samples. Pitch-fiber organized more than the ISO microstructure of charred resin matrix. On the other, PAN-fiber became more ordered, but was organization was lower than pitch-fiber. Thermal conductivity increased for both (2-D, 3-D C/C) materials in comparison to non-heat treated (NHT) C/Cs. Thermal conductivity of oxidized samples decreased significantly than non-oxidized samples. In-plane thermal conductivity of 3-D C/C was much higher than that of 2-D C/C, and was attributed to the rough laminar (RL) microstructure of carbon matrix and continuous PAN-fiber when compared to the short pitch-fiber in isotropic (ISO) carbon matrix. Mechanical properties (tensile, compressive, shear) deteriorated with increasing heat treatment. However, statistical analysis using ANOVA showed that there was not any significant difference between the NHT and heat treated C/C materials in terms of mechanical strength, modulus, failure strain and fracture energy. The oxidized samples of heat treated (1800/2100/2400 oC) C/C materials (2-D, 3-D) showed an appreciable decrease in mechanical strength and modulus than non-oxidized samples, with progressively heat treated C/C becoming more oxidation resistant than NHT C/C. The study demonstrated a highly inhomogeneous nature of C/C, and sample size is a very important parameter in governing mechanical properties. Since, the slightest change in the dimension of samples could bring about a radically different outcome in terms of mechanical properties, and can hardly be representative of the bulk properties. Therefore, in order to obtain a good estimate of the bulk properties, the sample size must be comparable to the bulk material. The research nonetheless showed the impact of sample size in estimating the mechanical properties of bulk properties, which are highly significant after statistical analysis, and, therefore, it must be taken into account to understand the processing-structure-property-analysis relationships.
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Forsberg, Niklas. "What affects the tear strength of paperboard? : Consequences of unbalance in a designed experiment." Thesis, Karlstads universitet, Handelshögskolan, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-63985.

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This essay covers a designed experiment on paperboard where the quality under study is tear strength alongside and across. The objective is to examine what consequences the loss of balance in a designed experiment has on the explanatory power of the proposed empirical model. As did happen, the trial plan didn’t go as planned when the first run caused a disruption of the paperboard in the machine. Decision from the company was to raise the low level of one of the design factors to prevent this from happening again. The consequence of this is an alteration of the design during ongoing experimentation. This in turn affects what analysis approaches are appropriate for the problem. Three different approaches for analyzing the data are presented, each with different propositions on how to deal with the complication that occurred. The answer to the research question is that the ability of the empirical model to discover significant effects is moderately weakened by the loss of one run (out of eight total). The price payed for retrieving less information from the experiment is that the empirical model, for tear strength across, doesn’t deem the effects significant at the same level as for the candidate model with eight runs. Instead of concluding that the main effect of  and the interaction effect  is significant at the 2%- and 4%-level, respectively, we must now settle with deeming them significant at the 6%- and 7%-level.
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Libros sobre el tema "Statistical (ANOVA)"

1

ANOVA: Repeated measures. Sage Publications, 1992.

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Jackson, Sally Ann. Random factors in ANOVA. Sage Publications, 1994.

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Rutherford, Andrew. ANOVA and ANCOVA: A GLM approach. 2nd ed. Wiley, 2011.

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Rutherford, Andrew, and Andrew Rutherford. ANOVA and ANCOVA: A GLM approach. 2nd ed. Wiley, 2011.

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Beyond ANOVA, basics of applied statistics. Wiley, 1986.

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Wm, Brown Byron, ed. Beyond ANOVA: Basics of applied statistics. Chapman & Hall, 1997.

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S, Fidell Linda, ed. Experimental designs using ANOVA. Thomson/Brooks/Cole, 2007.

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Goos, Peter. Statistics with JMP: Hypothesis tests, ANOVA, and regression. John Wiley & Sons, Inc., 2016.

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Population by sex, age, religion, ethnicity according to district and D.S. Division (provisional): Strī puruṣa bhāvaya, vayasa, āgama, janavargaya anuva distrikk saha Prā. Lē. koṭṭhāśayvala janagahanaya (yāvakālika) = Āṇ-peṇ pirivu, vayatu, samaya, ena rītiyaga māvaṭṭa mar̲r̲um pirateca ceyalāḷar pirivuritiyān̲a sanatogai (tharkaligamanattu). Dept. of Census and Statistics, 2001.

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Statistical Modeling, Linear Regression and ANOVA: A Practical Computational Perspective. Lulu.com, 2018.

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Capítulos de libros sobre el tema "Statistical (ANOVA)"

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Ross, Amanda, and Victor L. Willson. "Factorial Anova." In Basic and Advanced Statistical Tests. SensePublishers, 2017. http://dx.doi.org/10.1007/978-94-6351-086-8_6.

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Akritas, Michael G. "Nonparametric Models for ANOVA and ANCOVA Designs." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_415.

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Ross, Amanda, and Victor L. Willson. "One-Way Anova." In Basic and Advanced Statistical Tests. SensePublishers, 2017. http://dx.doi.org/10.1007/978-94-6351-086-8_5.

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Green, Rita. "Comparing Performance III: ANOVA." In Statistical Analyses for Language Testers. Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137018298_8.

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Reddy, M. Venkataswamy. "Experimental Data Analysis: Anova." In Statistical Methods in Psychiatry Research and SPSS. Apple Academic Press, 2019. http://dx.doi.org/10.1201/9780429023309-10.

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Frude, Neil. "Statistical Analysis IV: ONEWAY and ANOVA." In A Guide to SPSS/PC+. Macmillan Education UK, 1993. http://dx.doi.org/10.1007/978-1-349-13164-8_12.

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Frude, Neil. "Statistical Analysis IV: ONEWAY and ANOVA." In A Guide to SPSS/PC+. Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4757-8985-0_12.

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Frude, Neil. "Statistical Analysis IV: ONEWAY and ANOVA." In A Guide to SPSS/PC+. Palgrave Macmillan UK, 1987. http://dx.doi.org/10.1007/978-1-349-09709-8_12.

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Lawal, Bayo. "Analysis of Variance (ANOVA)." In Applied Statistical Methods in Agriculture, Health and Life Sciences. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05555-8_6.

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Armstrong, Richard A., and Anthony C. Hilton. "One-Way Analysis of Variance (Anova)." In Statistical Analysis in Microbiology: Statnotes. John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9780470905173.ch6.

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Actas de conferencias sobre el tema "Statistical (ANOVA)"

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Mu, Weiyan, and Xiaona Yuan. "Statistical inference for ANOVA under heteroscedasticity: Statistical inference." In 2012 2nd International Conference on Consumer Electronics, Communications and Networks (CECNet). IEEE, 2012. http://dx.doi.org/10.1109/cecnet.2012.6201745.

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Salami, Abbas, Farnaz Ghassemi, and Mohammad Hasan Moradi. "A Criterion to Evaluate Feature Vectors Based on ANOVA Statistical Analysis." In 2017 24th National and 2nd International Iranian Conference on Biomedical Engineering (ICBME). IEEE, 2017. http://dx.doi.org/10.1109/icbme.2017.8430266.

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Tavares, Lucas Ramos, Tatiane S. Costa, Karen Barbosa de Melo, Joao Lucas de S. Silva, and Marcelo G. Villalva. "Statistical analysis ANOVA and MANOVA of irradiation and temperature database for photovoltaic systems." In 2020 IEEE International Conference on Industrial Technology (ICIT). IEEE, 2020. http://dx.doi.org/10.1109/icit45562.2020.9067233.

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Stan, Felicia, Daniel Vlad, and Catalin Fetecau. "Statistical Cutting Force Model for Orthogonal Cutting of Polytetrafluoroethylene (PTFE) Composites." In ASME 2013 International Manufacturing Science and Engineering Conference collocated with the 41st North American Manufacturing Research Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/msec2013-1033.

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This paper presents an experimental investigation of the cutting forces response during the orthogonal cutting of polytetrafluoroethylene (PTFE) and PTFE-based composites using the Taguchi method. Cutting experiments were conducted using the L27 orthogonal array and the effects of the cutting parameters (feed rate, cutting speed and rake angle) on the cutting force were analyzed using the S/N ratio response and the analysis of variance (ANOVA). Statistical models that correlate the cutting force with process variables were developed using ANOVA and polynomial regression. The variation of the apparent friction coefficient was analyzed with respect to tool geometry and the cutting process. The results indicated that cutting and thrust forces increase with increasing feed rate, and decrease with increasing rake angles from negative to positive values and increasing cutting speed. A power law relationship between the apparent friction coefficient and the normal force exerted by the chip on the tool-rake face was identified, the former decreasing with an increasing normal force.
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Dimitriou, Pavlos, Zhijun Peng, David Lemon, Bo Gao, and Michail Soumelidis. "Diesel Engine Combustion Optimization for Bio-Diesel Blends Using Taguchi and ANOVA Statistical Methods." In 11th International Conference on Engines & Vehicles. SAE International, 2013. http://dx.doi.org/10.4271/2013-24-0011.

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Booth, J. E., K. D. Nelson, T. J. Harvey, R. J. K. Wood, J. G. Martinez, and H. E. G. Powrie. "Mini-Traction-Machine Tests to Assess the Effect of Base Oil and Additive Interactions on Surface Charge and Friction." In ASME/STLE 2007 International Joint Tribology Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/ijtc2007-44317.

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Electrostatic condition monitoring was implemented on a MTM to examine the influence of additive adsorption from three base oils. Statistical analysis (ANOVA) indicates significant affects on measured charge and friction levels for both additive and base oil type.
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Karakhan, Ali, John Gambatese, Kasim Alomari, and Ding Liu. "Consideration of Worker Safety in the Design Process: A Statistical-Based Approach Using Analysis of Variance (ANOVA)." In Construction Research Congress 2018. American Society of Civil Engineers, 2018. http://dx.doi.org/10.1061/9780784481288.037.

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Balta, Berna, Fazıl O¨nder So¨nmez, and Abdu¨lkadir Cengiz. "Gage Repeatability and Reproducibility Investigations of a Test Rig Using ANOVA/Xbar-R Method." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-62130.

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In an experimental study, good measurement systems are important for approaching successful decisions. The assessment of a measurement system is known as “Gage Repeatability and Reproducibility” (GR&amp;R). “Measurement System Analysis” (MSA) should be performed at the beginning of an experimental study to ensure that the information to be collected are true representation of what is occurring in the experiment. Experimental data collected under the same condition usually show variation, which arises partly from the experimental system, partly from the measurement devices and partly from the operator who makes the measurements. MSA helps to differentiate the contribution of each source to the randomness of the data. In this way, one may see whether there is a need to reduce the measurement variation so that the data reflects basically the experimental variation. Besides, MSA gives quantitative measures for repeatability and reproducibility. Repeatability is the variation in repeated measurements taken by the same operator under the same experimental conditions. Reproducibility is the variation in data obtained by different operators taking the measurement with the same setup under the same conditions. These are measures of the consistency and precision of the data. GR&amp;R is the most common MSA tool that analyzes the viability of an experimental set-up. Resultant GR&amp;R will indicate overall measurement system variation as the sum of repeatability variation and reproducibility variation. Generally, GR&amp;R % gives a measure of the suitability of the measurement system to yield acceptable data for statistical studies such as “Design Of Experiments” (DOE), “One Factor At a Time” (OFAT), “Response Surface Methodology”, etc. [1, 2]. In this paper, “Analysis of Variance” (ANOVA) and the “Average and Range” (Xbar &amp; R) methods are used to assess the capability of a laboratory made measurement device, which is used for the investigations of a belt drive system efficiency. GR&amp;R is applied at the design stages of the construction of the test rig and final application is presented in this study. The results prove that the test rig is capable of making experimental studies using statistical methods such as DOE and Response Surface Methodology.
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Mohammadi, Aminollah, Alireza Fadaei Tehrani, Davoud Karimi, and Ehsan Emanian. "A New Approach in Surface Roughness and Roundness Improvement in Wire Electrical Discharge Turning Based on Statistical Analyses." In ASME 2006 International Manufacturing Science and Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/msec2006-21001.

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In this paper, the effects and optimization of machining parameters on surface roughness and roundness in turning by wire EDM process are investigated. Surface roughness and roundness, were chosen, as the machining parameters to verify the process. In addition, power, time-off, voltage, servo, wire speed, wire tension and rotational speed were adopted for evaluation by Taguchi method. A L18 (21 × 37) Taguchi standard orthogonal array is chosen for the design of experiments. The level of importance of the machining parameters on the surface roughness and roundness is determined by using analysis of variance (ANOVA). The optimum machining parameters combination was obtained by using the analysis of signal-to-noise (S/N) ratio. The variation of surface roughness and roundness with machining parameters is mathematically modeled by using regression analysis method. Finally, experimentation was carried out to identify the effectiveness of the proposed method. A good improvement was obtained.
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10

Bhende, Gaurav P., Pallavi B. Kulkarni, and Priyanka M. Kale. "Analyzing Effects of Soil Parameters on Buried Pipe Behavior and Deciding Governing Parameter Using Statistical Approach." In ASME 2015 India International Oil and Gas Pipeline Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/iogpc2015-7908.

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One of the most common and practical difficulties a pipeline engineer faces at the initial stage of the project is the lack of Soil survey data. Hence, various soil parameters like soil type, density, friction angle, cohesive pressure, depth of cover, pipe coating etc. are needed to be assumed. The critical designs like anchor block requirement, pipe route changes, support loads which involve a huge cost are required to be ‘Issued for Construction’ based on assumed data. This paper briefly illustrates and compares the results obtained from the two most common buried pipe stress analysis methods viz. ‘American Lifeline Alliance - Appendix B’ (1) and ‘Stress Analysis Methods for Underground Pipelines’ (2) and shows their effects graphically on the various Stress Analysis results like pipe movement, end force, active length (virtual anchor length) and bending stress generated in the buried pipeline. Further, this paper comes up with an unique application of ANOVA, a Statistical method, to find out the most significant soil parameter affecting the said results. The paper explains this method with a solved example. These results are useful for a pipeline engineer to determine the governing soil parameter in the design and thus provide a useful tool to make optimum assumptions in absence of soil data so as to minimize the changes in future design and helps saving the cost of the project due to rework.
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Informes sobre el tema "Statistical (ANOVA)"

1

Kim, Joseph J., Samuel Dominguez, and Luis Diaz. Freight Demand Model for Southern California Freeways with Owner–Operator Truck Drivers. Mineta Transportation Institute, 2020. http://dx.doi.org/10.31979/mti.2020.1931.

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This study evaluates the demand for truck-only toll lanes on Southern California freeways with owner–operator truck drivers. The study implemented the stated preference survey method to estimate the value placed by drivers on time, reliability, and safety measures using various scenarios geared towards assessing those values. The project team met face-to-face with owner- operator truck drivers near the Ports of Los Angeles and Long Beach to understand the drivers’ perspectives regarding truck-only toll lanes on Southern California freeways. A data set containing 31 survey responses is obtained and used for statistical data analysis using analysis of variable (ANOVA) and two sample t-tests. The analysis results showed that 75.27% of the owner– operator truck drivers responded are willing to pay toll fees when they choose routes. The tolerated average toll fees are $13.77/ hr and $12.82/hr for weekdays and weekends, respectively. The analysis results also showed that owner–operator truck drivers will take truck-only toll lanes when they take the routes used in four comparisons out of six comparisons according to the three measures such as values of time, reliability, and safety, despite sharing a common origin and destination. The highest toll fee per mile on any day that drivers are willing to pay when the main factor being compared is value of time is $0.31/mile or $18.35/hr. The toll fees associated with reliability and safety measures are $0.30/mile or $8.94/hr and $0.22/mile or $11.01/hr, respectively. These results are meaningful for legislators and transportation agencies as the behaviors and route choice characteristics of owner–operator truck drivers help them better understand the utility and demand for truck-only toll lanes.
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Tucker-Blackmon, Angelicque. Engagement in Engineering Pathways “E-PATH” An Initiative to Retain Non-Traditional Students in Engineering Year Three Summative External Evaluation Report. Innovative Learning Center, LLC, 2020. http://dx.doi.org/10.52012/tyob9090.

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The summative external evaluation report described the program's impact on faculty and students participating in recitation sessions and active teaching professional development sessions over two years. Student persistence and retention in engineering courses continue to be a challenge in undergraduate education, especially for students underrepresented in engineering disciplines. The program's goal was to use peer-facilitated instruction in core engineering courses known to have high attrition rates to retain underrepresented students, especially women, in engineering to diversify and broaden engineering participation. Knowledge generated around using peer-facilitated instruction at two-year colleges can improve underrepresented students' success and participation in engineering across a broad range of institutions. Students in the program participated in peer-facilitated recitation sessions linked to fundamental engineering courses, such as engineering analysis, statics, and dynamics. These courses have the highest failure rate among women and underrepresented minority students. As a mixed-methods evaluation study, student engagement was measured as students' comfort with asking questions, collaboration with peers, and applying mathematics concepts. SPSS was used to analyze pre-and post-surveys for statistical significance. Qualitative data were collected through classroom observations and focus group sessions with recitation leaders. Semi-structured interviews were conducted with faculty members and students to understand their experiences in the program. Findings revealed that women students had marginalization and intimidation perceptions primarily from courses with significantly more men than women. However, they shared numerous strategies that could support them towards success through the engineering pathway. Women and underrepresented students perceived that they did not have a network of peers and faculty as role models to identify within engineering disciplines. The recitation sessions had a positive social impact on Hispanic women. As opportunities to collaborate increased, Hispanic womens' social engagement was expected to increase. This social engagement level has already been predicted to increase women students' persistence and retention in engineering and result in them not leaving the engineering pathway. An analysis of quantitative survey data from students in the three engineering courses revealed a significant effect of race and ethnicity for comfort in asking questions in class, collaborating with peers outside the classroom, and applying mathematical concepts. Further examination of this effect for comfort with asking questions in class revealed that comfort asking questions was driven by one or two extreme post-test scores of Asian students. A follow-up ANOVA for this item revealed that Asian women reported feeling excluded in the classroom. However, it was difficult to determine whether these differences are stable given the small sample size for students identifying as Asian. Furthermore, gender differences were significant for comfort in communicating with professors and peers. Overall, women reported less comfort communicating with their professors than men. Results from student metrics will inform faculty professional development efforts to increase faculty support and maximize student engagement, persistence, and retention in engineering courses at community colleges. Summative results from this project could inform the national STEM community about recitation support to further improve undergraduate engineering learning and educational research.
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