A new method for the analysis of a multivariate dataset depending on several factors is proposed. It is called AoV-PLS (Analysis of VariancePLS). It is based on the decomposition of the dataset into ...the main effects, the interactions effects and possibly the residual matrix using a model akin to analysis of variance (ANOVA). Each effect is considered in turn and assessed through the use of a Partial Least Square regression (PLS-regression). The connection of AoV-PLS to competing methods such as ANOVA-PCA and ANOVA-Simultaneous Component Analysis (ASCA) is emphasized and these methods are compared on the basis of a dataset pertaining to metabolomics field.
Experimental statistics are a key element for innovation in the agricultural sector. Commonly used statistical methods in experimentation are relatively simple, reliable, and widely used. However, ...the many problems in the quality of statistical analyses reported in the agricultural science literature highlight a need for continuing discussion on and updating of this topic. This article reviews critical points about classic linear models procedures commonly used in agricultural statistics, frequent procedures in publications in the agricultural sciences. Due to the evolution of statistical science some common recommendations from the past should no longer be followed.
Fused Deposition Modelling (FDM) is one type of additive manufacturing process, where the product is manufactured through layer by layer addition process with high accuracy using computer aided ...design data. 3-D printing technology is a growing sector of manufacturing, automotive, aerospace and many others. In all these fields it’s proven as the cost effective. In this research work, the 3D printed parts are designed according to ASTM standards and printed from a digital template file using the FDM machine. The material chosen for this 3-D printing parameter optimization is Nylon. In order to improve mechanical properties, tests like Ultimate Tensile Strength (UTS), impact strength, flexural strength and shore D hardness were processed through Taguchi L9 orthogonal array, It have been used with varying the input parameters like fill Density (FD) , Layer Height (LH) and Print Speed (PS). To study the influence of output parameters with respect to input parameters Analysis of Variance (ANOVA) was employed.
Analysis of variance (ANOVA) is widely used to assess the influence of one or more experimental (or quasi-experimental) manipulations on a continuous outcome. Traditionally, ANOVA is carried out in a ...frequentist manner using p values, but a Bayesian alternative has been proposed. Assuming that the proposed Bayesian ANOVA is closely modeled after its frequentist counterpart, one may be surprised to find that the two can yield very different conclusions when the design involves multiple repeated-measures factors. We illustrate such a discrepancy with a real data set from a two-factorial within-subject experiment. For this data set, the results of a frequentist and Bayesian ANOVA are in a disagreement about which main effect accounts for the variance in the data. The reason for this disagreement is that frequentist and the proposed Bayesian ANOVA use different model specifications. As currently implemented, the proposed Bayesian ANOVA assumes that there are no individual differences in the magnitude of effects. We suspect that this assumption is neither obvious to nor desired by most analysts because it is untenable in most applications. We argue here that the Bayesian ANOVA should be revised to allow for individual differences. As a default, we suggest the standard frequentist model specification but discuss a recently proposed alternative and provide guidance on how to choose the appropriate model specification. We end by discussing the implications of the revised model specification for previously published results of Bayesian ANOVAs.
Industries use heat treated steel for various components due to its strength and other mechanical properties. Usually hardening of machining is carried out by energy and cost intensive grinding ...process. Recently, hard machining has replaced grinding for certain specific applications. In this study, Cubic boron nitride (CBN) of specification CNMG120408is employed to machine AISI D2 steel of 46 HRC hardness. Nine machining experiments established by L9 orthogonal array were conducted. Surface roughness and cutting force were taken as response variables. From the signal to noise ratio analysis, the optimum combination of cutting process parameters for surface roughness is found out to be 80 m/min (Cutting speed) 0.109 mm/rev (Feed) and 0.1 mm (depth of cut). From Analysis of variance (ANOVA), the share made by every process parameter on the machining performance is found out for this CBN tool-work piece combination. Feed rate has the maximum contribution (56 %) for main cutting force while Cutting speed has the maximum contribution (72 %) for surface roughness. Cutting speed exerts greater influence on surface finish compared to feed rate in hard machining.
The thermoelectric generator (TEG) can directly convert heat to electricity. However, its efficiency is low, so optimizing TE systems to maximize output power is necessary. Many review papers have ...focused on this technology. However, there has not been a comprehensive review of TEG optimization by a statistical approach. This study reviews thermoelectric generator optimization by the Taguchi method, analysis of variance (ANOVA), and the response surface methodology (RSM) to identify the major optimization findings and tendencies for this technology. Three optimization paths are identified: operating conditions, geometrical configuration, and TE materials for thermoelectric generators (TEGs). Although there is no “one-size-fits-all” combination of characteristics that a TEG system should have, some tendencies based on the results of previous studies have been identified. The key parameters that show the most significant effect on the TEG system for each optimization path are the heat source temperature for the operating conditions and the TE leg height for the geometrical configuration. However, there are no distinctly recognized parameters for TE materials. Thus, these results show that optimizing the heat source conditions of a TEG system will yield the best possible results, and optimizing the TE leg height in the TE module would further improve the system. About 70% of the studies optimizing thermoelectric generators utilized the Taguchi method; thus, the Taguchi method remains the most popular statistical tool for TEG analysis. Finally, the perspectives and challenges of optimizing thermoelectric generators using statistical approaches are underlined.
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•This study reviewers thermoelectric generator optimization by the Taguchi method, ANOVA, and RSM.•Three optimization paths via operating conditions, geometry, and materials are identified.•The review shows that hot-side temperature and TE leg length are the most influential parameters.•No tendency for the optimization of the thermoelectric material properties has been identified.•Mixing different optimization methods gives the most complete analysis of a given system.
Response surface methodology (RSM) is used to optimize the process parameters in casting, welding and machinability studies of composite materials. Response surface methodology is commonly used to ...design the experiments and it minimizes the numbers of experiments for specific number of factors and its levels. It has many advantages over Taguchi method of design. Experiments are conducted as per the experimental design and the responses such as output is recorded. Analysis of variance is used to identify the factors which significantly influence the response. Regression equations are developed to predict the response and the process parameters are optimised for obtaining a specific objective function.
We consider two questions important for applying analysis of variance (ANOVA): Should normality be checked on the raw data or on the residuals (or is it immaterial which of the two approaches we ...take)? Should normality and homogeneity of variance be checked using significance tests or diagnostic plots (or both)? Based on two examples, we show that residuals should be used for model checking and that residual plots are better for checking ANOVA assumptions than statistical tests. We also discuss why one should be very cautious when using statistical tests to check the assumptions.
In this paper, significant results about the evaluation of the influence of wear test factors such as load, distance, and sliding speed are analyzed to determine the statistical behavior of the ...specific wear rate, depth, and friction coefficient as response variables. Dry sliding wear tests were performed on the borided AISI 316L stainless steel under controlled environmental conditions, according to the ASTM G133-05 standard procedure, and a UMT-2 universal tester was used. The development of the analysis of variance showed that the load factor has the major statistical significance on the specific wear rate, depth, and CoF with 63.7%, 59.60%, and 62.67%, respectively. The response surface methodology was applied through the distance weighted least-squares fitting to explain the behavior of the response variables on the measured variables and the difference in the performance due to the total distance of sliding.
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•Dry sliding wear statistical analysis on borided AISI 316L stainless steel under ball-on-flat tests was investigated.•The load factor has the major statistical significance with 63.7% on the specific wear rate.•A full factorial design randomized experiment approach was applied to study the test factors and levels.•RSM with DWLS was applied to obtain 2D maps of the response variables.
Custom Contrast Testing Guggenmos, Ryan D.; Piercey, M. David; Agoglia, Christopher P.
The Accounting review,
09/2018, Letnik:
93, Številka:
5
Journal Article
Recenzirano
Contrast analysis has become prevalent in experimental accounting research since Buckless and Ravenscroft (1990) introduced it to the accounting literature over 25 years ago. Since its initial ...introduction, the scope of contrast testing has expanded, yet guidance as to the most appropriate methods of specifying, conducting, interpreting, and exhibiting these tests has not. We survey the use of contrast analysis in the recent literature and propose a three-part testing approach that provides a more comprehensive picture of contrast results. Our approach considers three pieces of complementary evidence: the visual evaluation of fit, traditional significance testing, and quantitative evaluation of the contrast variance residual. Our measure of the contrast variance residual, 𝑞², is proposed for the first time in this work. After proposing our approach, we walk through six common contrast testing scenarios where current practices may fall short and our approach may guide researchers. We extend Buckless and Ravenscroft (1990) and contribute to the accounting research methods literature by documenting current contrast analysis practices that result in elevated Type I error and by proposing a potential solution to mitigate these concerns.
