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Statistical Analysis for the Abrasive Wear Behavior of Al 6061  [PDF]
Mohd Shadab Khan, Zahir Hasan, Yaqoob Ali Ansari
Journal of Minerals and Materials Characterization and Engineering (JMMCE) , 2014, DOI: 10.4236/jmmce.2014.24034
Abstract: In the present study, a mathematical model has been developed to predict the abrasive wear behavior of Al 6061. The experiments have been conducted using central composite design in the design of experiments (DOE) on pin-on-disc type wear testing machine, against abrasive media. A second order polynomial model has been developed for the prediction of wear loss. The model was developed by response surface method (RSM). Analysis of variance technique at the 95% confidence level was applied to check the validity of the model. The effect of volume percentage of reinforcement, applied load and sliding velocity on abrasive wear behavior was analyzed in detail. To judge the efficiency and ability of the model, the comparison of predicted and experimental response values outside the design conditions was carried out. The result shows, good correspondence, implying that, empirical models derived from response surface approach can be used to describe the tribological behavior of the above composite.
New Method for Optimization and Simultaneous Determination of Sparfloxacin and Non Steroidal Anti-Inflammatory Drugs: Its In-Vitro Application  [PDF]
Somia Gul, Najma Sultana, Muhammad Saeed Arayne, Sana Shamim, Mahwish Akhtar
American Journal of Analytical Chemistry (AJAC) , 2012, DOI: 10.4236/ajac.2012.34045
Abstract: A simple reversed phase HPLC method was developed and validated for the simultaneous determination of sparfloxacin (SPFX), diclofenac sodium, meloxicam, ibuprofen, flurbiprofen, naproxen and mefenemic acid in a relatively short time with high linearity in bulk material, pharmaceutical formulations and human serum. Purospher STAR C18 (250 × 4.6 mm, 5 μm) column was utilized with mobile phase, methanol and water (90:10, v/v pH 2.70 adjusted by phosphoric acid), was delivered at a flow rate of 1.5 mL.min–1. Eluent was monitored using UV detector at 240 nm. The proposed method is specific, accurate (98.42% - 102.75%), precise (intra-day and inter-day variation 0.011% - 1.85%) and linear (R2 > 0.999) with in the desired range 0.15 - 40 μg.mL–1 and the detection and quantification limit was 1.19E+08 – 0.150 μg.mL–1 and 3.62E+08 – 0.4574 μg.mL–1 respectively for SPFX and NSAIDs. The analysis of variance (ANOVA) and student’s t-test were applied to verify the results. The anticipated method is applicable to routine analysis of SPFX and NSAIDs in pharmaceutical formulations as well as in human serum samples. It has also applied on interaction of SPFX with NSAIDs.
Study of Halophytes Dispersion in the North-West Region of Algeria  [PDF]
Chahrazed Hassaine, Rédda Aboura, Abdessamad Merzouk, Djamel Benmansour
Open Journal of Ecology (OJE) , 2014, DOI: 10.4236/oje.2014.410053
Abstract:

To know the mode of distribution of halophytes species in the western region of Algeria, it was considered useful to undertake a study based on the achievement of identified linear. Two areas were considered, Northern Tlemcen (Beni Saf and Rachgoun) and Northwest Oran (Sabkha). The trend of climate aridity which is more pronounced in the study area may have influences on floristic halophytes. The study of the floristic composition showed the importance of indicator halophitisation species such as Atriplex halimus, Tamarix gallica, Salicornia fruticosa, Arthrocnemum glaucum and was accompanied by various therophytes such as Sinapis arvensis, Erodium moschatum, Malva sylvestris and Plantago lagopus. ANOVA (analysis of variance) has highlighted the factors that influence the spatial distribution of some halophytes species at five stations studied; some are dispersed aggregates (Tamarix gallica, Suaeda fruticosa) with a coefficient of variation (Cv) greater than 10%; others are regularly dispersed (Atriplex halimus) with a coefficient of variation (Cv) less than 10%.

Eliminating Aggregation Bias in Experimental Research: Random Coefficient Analysis as an Alternative to Performing a by-subjects and/or by-items ANOVA
Glenn L. Thompson
Tutorials in Quantitative Methods for Psychology , 2008,
Abstract: Experimental psychologists routinely simplify the structure of their data by computing means for each experimental condition so that the basic assumptions of regression/ANOVA are satisfied. Typically, these means represent the performance (e.g. reaction time or RT) of a participant over several items that share some target characteristic (e.g. Mean RT for high-frequency words). Regrettably, analyses based on such aggregated data are biased toward rejection of the null hypothesis, inflating Type-I error beyond the nominal level. A preferable strategy for analyzing such data is random coefficient analysis (RCA), which can be performed using a simple method proposed by Lorch and Myers (1990). An easy to use SPSS implementation of this method is presented using a concrete example. In addition, a technique for evaluating the magnitude of potential aggregation bias in a dataset is demonstrated. Finally, suggestions are offered concerning the reporting of RCA results in empirical articles.
Análisis bayesiano de variables relacionadas con el desarrollo del síndrome de Burnout en profesionales sanitarios
Ca?adas,Guillermo A.; Lozano,Luis M.; Fuente,Emilia I. de la; Vargas,Cristina; Salda?a,Lorena;
Escritos de Psicología (Internet) , 2010,
Abstract: burnout syndrome has a high incidence among professional healthcare and social workers. this leads to deterioration in the quality of their working life and affects their health, the organization where they work and, via their clients, society itself. given these serious effects, many studies have investigated this construct and identified groups at increased risk of the syndrome. the present work has 2 main aims: to compare burnout levels in potential risk groups among professional healthcare workers; and to compare them using standard and bayesian statistical analysis. the sample consisted of 108 psycho-social care workers based at 2 centers run by the granada council in spain. all participants, anonymously and individually, filled in a booklet that included questions on personal information and the spanish adaptation of the maslach burnout inventory (mbi). standard and bayesian analysis of variance were used to identify the risk factors associated with different levels of burnout. it was found that the information provided by the bayesian procedure complemented that provided by the standard procedure.
Análisis bayesiano de variables relacionadas con el desarrollo del sindrome de Burnout en profesionales sanitarios (Bayesian analysis of variables related to the developmentof Burnout syndrome in health professionals)
Guillermo A. Ca?adas,Luis M. Lozano,Emilia I. de la Fuente,Cristina Vargas
Escritos de Psicología , 2010,
Abstract: Burnout syndrome has a high incidence among professional healthcare and social workers. This leads to deterioration in the quality of their working life and affects their health, the organization where they work and, via their clients, society itself. Given these serious effects, many studies have investigated this construct and identified groups at increased risk of the syndrome. The present work has 2 main aims: to compare burnout levels in potential risk groups among professional healthcare workers; and to compare them using standard and Bayesian statistical analysis. The sample consisted of 108 psycho-social care workers based at 2 centers run by the Granada Council in Spain. All participants, anonymously and individually, filled in a booklet that included questions on personal information and the Spanish adaptation of the Maslach Burnout Inventory (MBI). Standard and Bayesian analysis of variance were used to identify the risk factors associated with different levels of burnout. It was found that the information provided by the Bayesian procedure complemented that provided by the standard procedure.
Major-minor element analysis in some plant seeds consumed as feed in Turkey  [PDF]
Umran Hicsonmez, Canan Ozdemir, Sermin Cam, Ali Ozdemir, F. Serap Erees
Natural Science (NS) , 2012, DOI: 10.4236/ns.2012.45042
Abstract: In this study, samples (clover, oats, bean, green lentil, spinach, corn, red lentil and rice) taken from some seeds consumed as food by people and from plant seeds used as provender are examined. Element analysis (Al, B, Ba, Bi, Ca, Cd, Co, Cr, Cu, Fe, K, La, Mg, Mn, Na, Ni, Pb, Sn, Sr, Sb, Si, Ti, U, Zn and Zr) in these samples was measured by using ICP-OES. Ca, K and Mg as major elements in all samples are determined. As results of the element analysis, meaningful relations between the elements in seeds have been researched by making statistical comparisons using one way analysis of variance (ANOVA).
Homogeneity of Monthly Mean Air Temperature of the United Republic of Tanzania with HOMER  [PDF]
Philbert M. Luhunga, Edmund Mutayoba, Hashim K. Ng’ongolo
Atmospheric and Climate Sciences (ACS) , 2014, DOI: 10.4236/acs.2014.41010
Abstract:

The long-term climate datasets are widely used in a variety of climate analyses. These datasets, however, have been adversely impacted by inhomogeneities caused by, for example relocations of meteorological station, change of land use cover surrounding the weather stations, substitution of meteorological station, changes of shelters, changes of instrumentation due to its failure or damage, and change of observation hours. If these inhomogeneities are not detected and adjusted properly, the results of climate analyses using these data can be erroneous. In this paper for the first time, monthly mean air temperatures of the United Republic of Tanzania are homogenized by using HOMER software package. This software is one of the most recent homogenization software and exhibited the best results in the comparative analysis performed within the COST Action ES0601 (HOME). Monthly mean minimum (TN) and maximum (TX) air temperatures from 1974 to 2012 were used in the analysis. These datasets were obtained from Tanzania Meteorological Agency (TMA). The analysis reveals a larger number of artificial break points in TX (12 breaks) than TN (5 breaks) time series. The homogenization process was assessed by comparing results obtained with Correlation analysis and Principal Component analysis (PCA) of homogenized and non-homogenized datasets. Mann-Kendal non-parametric test was used to estimate the existence, magnitude and statistical significance of potential trends in the homogenized and non-homogenized time series. Correlation analysis reveals stronger correlation in homogenized TX than TN in relation to non-homogenized time series. Results from PCA suggest that the explained variances of the principal components are higher in homogenized TX than TN in relation to non-homogenized time series. Mann-Kendal non-parametric test reveals that the number of statistical significant trend increases

ExpDes: An R Package for ANOVA and Experimental Designs  [PDF]
Eric B. Ferreira, Pórtya P. Cavalcanti, Denismar A. Nogueira
Applied Mathematics (AM) , 2014, DOI: 10.4236/am.2014.519280
Abstract: Analysis of variance (ANOVA) is a usual way for analysing experiments. However, depending on the design and/or the analysis scheme, it can be a hard task. ExpDes, acronym for Experimental Designs, is a package that intends to turn such task easier. Devoted to fixed models and balanced experiments (no missing data), ExpDes allows user to deal with additional treatments in a single run, several experiment designs and exhibits standard and easy-to-interpret outputs. It was developed at the Exact Sciences Institute of the Federal University of Alfenas, Brazil. Stable versions of package ExpDes are available on CRAN (Comprehensive R Archive Network) since 2012. Based on users’ feedback, the package was used to illustrate graduation and post-graduation classes and to carry out data analysis, in Brazil and many other countries. Package ExpDes differs from the other R tools in its easiness in use and cleanliness of output.
Investigating the Effect of Supplementary Feeding on Carbohydrate Composition and Quantity of Royal Jelly  [PDF]
Dimitrios Kanelis, Chrysoula Tananaki, Vasilios Liolios, Maria-Anna Rodopoulou, Georgios Goras, Nikolia Argena, Andreas Thrasyvoulou
Open Journal of Applied Sciences (OJAppS) , 2018, DOI: 10.4236/ojapps.2018.84011
Abstract: One of the main practices followed by beekeepers during the production of royal jelly (RJ) is the artificial sugar feeding. In this study, the effect of carbohydrate supplementary feeding on the composition of the three main sugars (fructose, glucose, sucrose) and on the final quantity of the product was explored using one-way ANOVA and non-parametric tests. Also, the correlations among the parameters were examined. The average yield per colony for non-supplemented colonies (Group A) was 12.8 g, while the average content of fructose, glucose and sucrose was 4.32%, 3.78%, and 0.04%, respectively. For the colonies fed at the grafting day one time (Group B), these values were 12.76 g, 3.11%, 3.19% and 3.71%, and for the colonies fed from the insertion until the collection day (Group C), 12.81 g, 3.05%, 3.12% and 3.54% respectively. It should also be noted that the sucrose content in all samples from supplemented colonies was found greater than 1.97%. The statistical tests highlighted the impact of artificial feeding on fructose and glucose contents, while the produced quantity remained uninfluenced. Finally, the Spearman (rho) coefficient test showed statistically significantly negative correlation between the monosaccharides (fructose, glucose) and sucrose.
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