Resultados de búsqueda - "lineal regression"

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  1. 1

    Estudio del desgaste del flanco de carburos recubiertos y cermet durante el torneado de alta velocidad en seco del acero AISI 1045 por Zambrano Robledo, Patricia del Carmen, Hernández González, Luis Wilfredo, Pérez Rodríguez, Roberto, Guerrero Mata, Martha Patricia, Dumitrescu, L.

    Publicado 2011
    “…The results were analyzed using the variance analysis and lineal regression analysis in order to describe the relationship between the flank wear and machining time, obtaining the adjusted model equation. …”
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  2. 2

    Social Factors Contributing to the Development of Allostatic Load in Older Adults: A Correlational- Predictive Study por Morales Jinez, Alejandro, Gallegos Cabriales, Esther Carlota, D'Alonzo, Karen T., Ugarte Esquivel, Alicia, López Rincón, Francisco J., Salazar González, Bertha Cecilia

    Publicado 2018
    “…Sample size was estimated to contrast the no relation (R2 = 0) hypotheis in a multiple lineal regression model with 11 covariables, with a significance level of .05, power of 90% (.90), when coefficient of determination (R2) is .15, resulting in a sample of 131 older adults. …”
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  3. 3

    Association between depressive symptoms and psychosocial factors and perception of maternal self-efficacy in teenage mothers por Lara, Ma Asunción, Patiño, Pamela, Navarrete, Laura, Hernández, Zaira, Nieto, Lourdes

    Publicado 2017
    “…The following instruments were applied: Center for Epidemiologic Studies Depression Scale (CES-D), Post-partum Depression Predictors Inventory-Revised (PDPI-R), and Maternal Efficacy Questionnaire to 120 mothers under 20 during the first six months postpartum. Bivariate lineal regression and hierarchical linear regression analyses were used for the data analysis. …”
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  4. 4

    Dinámica de bosques de coníferas en Durango, México por Pimienta de la Torre, Dorian de Jesús

    Publicado 2005
    “…Abstract The general objective of the study was development of methodological systems for the characterization of the processes development of forest conifers in Pueblo Nuevo, Durango, used distance dependent competition indexes evaluate through models of growth and adjusted by the procedure of non lineal regression, and obtain the best indexes for conifers forests. …”
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  5. 5

    Dinámica de bosques de coníferas en Durango, México por Pimienta de la Torre, Dorian de Jesús

    Publicado 2005
    “…Abstract The general objective of the study was development of methodological systems for the characterization of the processes development of forest conifers in Pueblo Nuevo, Durango, used distance dependent competition indexes evaluate through models of growth and adjusted by the procedure of non lineal regression, and obtain the best indexes for conifers forests. …”
    Enlace del recurso
    Tesis
  6. 6

    Fenotipos de obesidad y su asociación con el polimorfismo Pro12Ala del gen PPARƴ2 en mujeres de 18 a 50 años. por Robles Camporredondo, Gabriela

    Publicado 2017
    “…With the results of their genetic analysis (rs1801282 polymorphism), obtained by PCR-RT, genotypic and allelic frequencies were calculated; subsequently the association between Pro12Ala polymorphism of PPAR2 gene with the obesity phenotypes identified in the study population was evaluated employing a lineal regression statistical model. Results: participants were cataloged like “Normal weight obese” (42%), “Metabolically healthy obese” (23%), “Metabolically unhealthy obese” (19%), “Normal weight lean” (14%) and “Metabolically obese normal weight” (2%). …”
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  7. 7

    Fenotipos de obesidad y su asociación con el polimorfismo Pro12Ala del gen PPARƴ2 en mujeres de 18 a 50 años. por Robles Camporredondo, Gabriela

    Publicado 2017
    “…With the results of their genetic analysis (rs1801282 polymorphism), obtained by PCR-RT, genotypic and allelic frequencies were calculated; subsequently the association between Pro12Ala polymorphism of PPAR2 gene with the obesity phenotypes identified in the study population was evaluated employing a lineal regression statistical model. Results: participants were cataloged like “Normal weight obese” (42%), “Metabolically healthy obese” (23%), “Metabolically unhealthy obese” (19%), “Normal weight lean” (14%) and “Metabolically obese normal weight” (2%). …”
    Enlace del recurso
    Tesis
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