Use Of Variance Analysis Research Articles

How psychological ownership over nutritional products affects purchase intentions of high-pressure working groups.

This study aims to investigate the influence of psychological ownership of nutritional products on the purchase intention of high-pressure working groups, as well as the underlying mechanisms and boundary conditions of this influence. This study aims to investigate the impact of psychological ownership of nutritional products on the purchase intention of high-pressure working groups, as well as the underlying mechanisms and boundary conditions of this influence. The research contributes through the use of variance analysis, mediation models, and moderation models on data from adult participants over the age of 18, across three experiments. Experiment 1, conducted on the Credamo platform, randomly recruited 285 participants, with 148 males (51.9%) and 137 females (48.1%), and the results indicated a direct impact of psychological ownership on purchase intention. Building upon this, Experiment 2, which also utilized the Credamo platform and recruited 280 participants consisting of 136 males (48.6%) and 144 females (51.4%), further revealed the mediating role of perceived value. Experiment 3, with 265 participants randomly recruited on the Credamo platform, including 131 males (49.4%) and 134 females (50.6%), identified the moderating effect of nutritional awareness. The theoretical contribution of this study lies primarily in its in-depth exploration of the impact of psychological ownership of nutritional products. By integrating the factors of perceived value and nutritional awareness, it provides a systematic explanation for better understanding the purchase intentions of high-pressure working groups. Additionally, this study offers valuable strategies for merchants to enhance the purchase intentions of high-pressure living groups.

AEGA: enhanced feature selection based on ANOVA and extended genetic algorithm for online customer review analysis.

Sentiment analysis involves extricating and interpreting people's views, feelings, beliefs, etc., about diverse actualities such as services, goods, and topics. People intend to investigate the users' opinions on the online platform to achieve better performance. Regardless, the high-dimensional feature set in an online review study affects the interpretation of classification. Several studies have implemented different feature selection techniques; however, getting a high accuracy with a very minimal number of features is yet to be accomplished. This paper develops an effective hybrid approach based on an enhanced genetic algorithm (GA) and analysis of variance (ANOVA) to achieve this purpose. To beat the local minima convergence problem, this paper uses a unique two-phase crossover and impressive selection approach, gaining high exploration and fast convergence of the model. The use of ANOVA drastically reduces the feature size to minimize the computational burden of the model. Experiments are performed to estimate the algorithm performance using different conventional classifiers and algorithms like GA, Particle Swarm Optimization (PSO), Recursive Feature Elimination (RFE), Random Forest, ExtraTree, AdaBoost, GradientBoost, and XGBoost. The proposed novel approach gives impressive results using the Amazon Review dataset with an accuracy of 78.60 %, F1 score of 79.38 %, and an average precision of 0.87, and the Restaurant Customer Review dataset with an accuracy of 77.70 %, F1 score of 78.24 %, and average precision of 0.89 as compared to other existing algorithms. The result shows that the proposed model outperforms other algorithms with nearly 45 and 42% fewer features for the Amazon Review and Restaurant Customer Review datasets.

Ganoderma және Trametes туысына жататын саңырауқұлақтарын терең өсіру жағдайындағы биомасса синтезі деңгейі бойынша скринингі

This article presents studies aimed at searching among the collection cultures of medicinal Ganoderma and Trametes fungal strains that are the most active in terms of growth rate and accumulation of biomass on nutrient media of various compositions. 27 strains of the genus G. lucidum of different geographical origins and 29 strains of the genus Trametes (Fr.) from the collection of mushrooms of the N.G. Kholodny Institute of Botany of the National Academy of Sciences of Ukraine were studied. The radial growth rate of vegetative mycelium of the studied strains and their cultural and morphological features of growth on different nutrient media were examined. Certain differences were established between G. lucidum and T. versicolor fungal strains in terms of the level of biomass accumulation on media with different carbon and nitrogen sources. All the studied strains are able to grow at different carbon and nitrogen sources. The use of variance analysis of two-factor experience made it possible to detail the influence of nutrient sources, biological characteristics of strains, or their interaction on biomass biosynthesis. Based on the study of the cultural and morphological features of mycelial colonies, the radial growth rate of vegetative mycelium, the level of biomass accumulation on six types of liquid nutrient media it was found that the most productive strains in terms of biomass accumulation were T. versicolor 353 and G. lucidum 1621, which were selected for further research.

Calibration of Optical Communication Systems Data by Optimal Use of Variance Analysis’s test

Statistical analyzes include a study of many societies’ characteristics that are data collection, organization, analysis, and analysis to get the aim with easy-to-understand diagrams and analytical drawings in return. In this paper, we will try to shed light on the most popular statistical methods, analysis of variance, and familiarize the reader with its types and how to choose the most appropriate data used during the various experiments. This paper deals with a brief outline of the species, and a practical application of communication data using statistical methods, where we found from the obtained results that the sensor provided for sensing low ranges has high sensitivity and high linearity in addition to the possibility of using it in extreme environments, which makes it a good choice for use in medical fields. As for the mathematical analysis, the analysis of the variance test supports the practical results, as there are no differences between the first and second groups (probability = 0.1832) nor between the second and third groups (probability = 0.1043), but there are statistically significant differences between the first and third groups (probability = 0.0054). The preference belongs to the third group (C) and as the best response on run 18 = 430.

On the applicability of ANOVA models for CATA data

Check-All-That-Apply (CATA) questions return binary data from every subject on each product and attribute. To compare multiple samples, Cochran’s Q test is widely used to analyze such two-way data, with pairwise comparisons being conducted using McNemar’s test, the special case of Cochran’s Q for two samples. In many applications, this approach is viable, however, in some, it has limitations, most notably (i) incomplete and/or imbalanced data; (ii) experimental designs; (iii) more complex hypotheses. If an analysis of variance (ANOVA) would be valid in the sense of respecting the nominal type I error rate, all these issues would be resolved at once. CATA data is obviously not normally distributed. Yet, comparing analyses using ANOVA and Cochran’s Q, we noted F-tests for balanced designs to provide p values very close to those from Cochran’s Q test, and they have been shown earlier to be at least approximately valid for Rate-All-That-Apply (RATA) data.We explore whether ANOVA indeed offers a robust analysis for CATA data. To that end, we determined the randomization distribution for the respective F- and t-tests for various (balanced complete) CATA studies and compared it to the corresponding parametric distribution. The respective distributions overlap closely, suggesting that ANOVA-based tests (overall and for pairwise comparisons) are indeed valid. A limitation is found in case of very low elicitation rates across products, which leads to distinct discreteness of the randomization distribution for paired comparisons and hence the potential for slightly invalid results. Yet, even in those cases, ANOVA-based tests seem to provide a reasonable approximation for most purposes. We further discuss the properties for decreasing numbers of subjects as well as showcase applications for imbalanced data and modeling in a study using an experimental design for the products. We conclude with guidance on when the use of ANOVA for CATA data is reasonable.

Basicity Optimization of KF/Ca-MgO Catalyst using Impregnation Method

This research aimed at determining the optimum value between calcination temperature (X1), calcination time (X2) and %wt KF (X3) toward optimum basicity of KF/Ca-MgO catalyst. Approximately 2-4%wt KF was added to the KF/Ca-MgO catalyst using the impregnation method to assist the Ca-MgO, at 450-550 ºC and a calcination time of 2-4 hours. Furthermore, its basicity was analyzed using Tanabe's titration method. The use of Variance Analysis (ANOVA), indicated that calcination temperature (X1) factor achieved the highest basicity of KF/Ca-MgO catalyst, as indicated by its high F-value (16.46262) and low p-value (0.0067). The correlation between each operating variables and the responses were shown in a mathematical equation. The optimization value is estimated by limiting the calcination temperature from 415.9 to 584.1 ºC, with a calcination time ranging from 1.32 to 4.68 hours, and %wt KF of 1.3182 to 4.6818 % that obtained 1.18 mmol/g for the optimal catalyst basicity.

A review on machinability of carbon fiber reinforced polymer (CFRP) and glass fiber reinforced polymer (GFRP) composite materials

Abstract Fiber reinforced polymer (FRP) composite materials are heterogeneous and anisotropic materials that do not exhibit plastic deformation. They have been used in a wide range of contemporary applications particularly in space and aviation, automotive, maritime and manufacturing of sports equipment. Carbon fiber reinforced polymer (CFRP) and glass fiber reinforced polymer (GFRP) composite materials, among other fiber reinforced materials, have been increasingly replacing conventional materials with their excellent strength and low specific weight properties. Their manufacturability in varying combinations with customized strength properties, also their high fatigue, toughness and high temperature wear and oxidation resistance capabilities render these materials an excellent choice in engineering applications. In the present review study, a literature survey was conducted on the machinability properties and related approaches for CFRP and GFRP composite materials. As in the machining of all anisotropic and heterogeneous materials, failure mechanisms were also reported in the machining of CFRP and GFRP materials with both conventional and modern manufacturing methods and the results of these studies were obtained by use of variance analysis (ANOVA), artificial neural networks (ANN) model, fuzzy inference system (FIS), harmony search (HS) algorithm, genetic algorithm (GA), Taguchi's optimization technique, multi-criteria optimization, analytical modeling, stress analysis, finite elements method (FEM), data analysis, and linear regression technique. Failure mechanisms and surface quality is discussed with the help of optical and scanning electron microscopy, and profilometry. ANOVA, GA, FEM, etc. are used to analyze and generate predictive models.

膏桐实生苗与扦插苗的抗旱性对比研究

近年来，云南遭受了百年不遇的严重旱灾，林业工程造林正面临着艰巨的考验，培育优良的抗旱树种及探索其抗旱机制显得尤为重要。因此，通过水分梯度法控水，我们从生长指标和生理生化指标等方面研究两种不同繁殖方式的膏桐(扦插苗与实生苗)的抗旱性，并利用SPSS软件进行方差分析和相关性分析、应用隶属函数法对其抗旱能力作出综合评价及比较。结果表明：1) 在不同程度干旱胁迫下，两种不同繁殖方式的膏桐苗木成活率均达到了100%，在重度干旱胁迫的中后期和末期部分叶片才出现了萎蔫、叶片卷曲、枯萎、落叶等现象；2) 膏桐实生苗和扦插苗的苗高生长均受到抑制，且随着干旱胁迫程度的加剧、时间的延长，苗高生长量受抑程度增加；3) 植株总干重、茎干重、叶干重和根干重均呈现下降趋势，与对照相比，膏桐实生苗上述指标的降幅均低于膏桐扦插苗；4) 与对照相比，膏桐实生苗及扦插苗苗木的根冠比都随着干旱胁迫强度的加强和胁迫时间的延长而呈现出明显的上升趋势；5) 苗木叶片相对含水量下降，下降幅度与干旱胁迫强度及时间成正比，且繁殖方式不同，下降幅度不同。由此可知：无论哪种繁殖方式的膏桐在干旱胁迫条件下苗木仍能维持较正常的生理过程，保持相对高的生长速率，抗旱能力较强。根据各项生长指标来判断，膏桐实生苗的抗旱生长略高于膏桐扦插苗。 In recent years, Yunnan had suffered from the worst drought in a century, and there was the big-gest challenge in front of the development of forestry industry, whereupon it would be particularly important for us to cultivate improved drought-resistant species and research its drought resistance mechanism. Therefore the drought resistance of two different modes of reproduction (seedlings and cuttings) of Jatropha curcas was researched from the growth indexes, physiological and biochemical indexes with the moisture gradient method to control water. And then the comprehensive evaluation and comparison of their drought resistance ability was made by use of variance analysis, correlation analysis and application method of subordinate function in SPSS software. The results showed that : 1) under the different degree of drought stress, the survival rate of those two different modes of reproduction seedlings were both up to 100%, and most of leaves didn’t appear wilting, leaf curl, fallen leaves at the middle, late and last phase until under the severe drought stress; 2) the growth in seedling height was restrained with the increase of drought stress degree and the extension of time; 3) the total dry weight of the plant, stem, leaves and root were all in downtrend, compared to check samples, the decline range of above indexes of cuttings of Jatropha curcas was lower than its seedlings; 4) compared to check samples, the root shoot ratio of those two different seedlings took on apparent uptrend along with the increase of drought stress degree and extension of time; 5) the relative water content of seedling leaves declined, and the decline range was in proportion to the degree of drought stress and the length of time. And those two modes of reproduction differed in the decline range. It can be seen that Jatropha curcas seedling in whatever kind of reproduction still could maintain its normal physiological process, maintain relatively high growth rate and drought resistance ability. According to the drought coefficient and the relative growth in seedling height, the drought-resistant growth of cuttings was a little higher than that of seedlings.

An Analysis on the Organization of Distressed ( Old ) Urban Texture with an Emphasis on Physical - Spatial Dimensions : Case Study : Karaj City

Uncontrolled and unplanned spatial expansion of cities large and medium in the past decades, causing the formation of new tissues in the vicinity of urban areas And the displacement of residents and urban areas are new. Therefore, replacement of old tissue gradually working and social life of cities - have lost their economic And the texture of urban life with the loss of their tendency towards stagnation and burnout have found. Karaj old texture of this study was selected as the study area, the main purpose of this study, social and economic characteristics of residents aged textured (Karaj) and understanding the physical condition of tissue. The research method according to research objectives and hypotheses is bibliographical - field method (observation, interview and questionnaire). In this study the sample size has been estimated with the use of Cochran's formula which is equal to 320 people and the sample has been selected with the use of random sampling method. Information and data have been analyzed with the used of Excel and SPSS with the use of variance analysis and Pearson's correlation coefficient statistical tests. According to data analysis, the results indicate that Limitations, the indigenous inhabitants of urban services and infrastructure migration from other parts of town Tissue and cause negative population growth over recent years has been On the other hand, because of socio_economic status of residents, texture, Has led to the improvement and modernization within the tissue, which causes wear to these factors and more tissue destruction is. Keywords: organization, dilapidated structure, urban land use, the city of Karaj

ONE-WAY ANALYSIS OF VARIANCE (ANOVA) IN STATA SOFTWARE

In the article, we have presented theoretical principles of one-way analysis of variance (ANOVA) for comparisons of three or more independent groups. Examples of the use of ANOVA with manual calculations using formulas have been given as well as algorithms of the use of ANOVA in STATA software. Special consideration has been given to the assumptions which have to be tested as well as the ways to present the results in research papers.

The Effects of Machining Parameters on Cutting Forces, Surface Roughness, Built-Up Edge (BUE) and Built-Up Layer (BUL) During Machining AA2014 (T4) Alloy

Tool wear, formed in cutting tool during machining processes, affects the surface roughness of the work piece, cutting forces and other output parameters. The effects of the machining parameters cutting speed (Vc) and the feed rate (f) on built-up edge (BUE), built-up layer (BUL), main cutting force (Fc), and surface roughness (Ra) is investigated in this study. The effects of the cutting parameters on cutting force and surface roughness has been examined by the use of Variance Analysis (ANOVA); and their optimum and critical cutting parameters were determined accordingly. AA2014 aluminum alloy was machined with uncoated carbide tools using Computer Numerical Control (CNC) turning machine under dry cutting conditions. Four different cutting speeds (200 m/min, 300 m/min, 400 m/min, and 500 m/min), five different feed rates (0.10 mm/rev, 0.15 mm/rev, 0.20 mm/rev, 0.25 mm/rev, and 0.30 mm/rev) and a constant depth of cut were selected as the machining parameters. BUE and BUL in the cutting tool were formed most at cutting speed 200 m/min and feed rate 0.30 mm/rev. The lowest cutting force was determined as 137 N at cutting speed 500 m/min and feed rate 0.10 mm/rev. The lowest average surface roughness, however, was determined as 0.93 µm at 500 m/min cutting speed and feed rate 0.10 mm/rev.

Association Analysis of Population-Based Quantitative Trait Data: An Assessment of ANOVA

The classical analysis of variance (ANOVA) compares the means of different groups under the assumption that the variances within each of the groups are equal. However, for genetic studies of complex disorders, it is not reasonable to assume that variance of a quantitative trait within each genotype at the trait locus will be equal. Thus, the use of ANOVA may lead to misleading association inferences. In this article, we perform a simulation-based study to assess the rate of false positives and the power of ANOVA under various probability distributions of the quantitative trait and different genetic parameters such as allele frequencies and coefficient of linkage disequilibrium.

Analysis of Variance Is Easily Misapplied in the Analysis of Randomized Trials: A Critique and Discussion of Alternative Statistical Approaches

Analysis of variance (ANOVA) is a statistical method that is widely used in the psychosomatic literature to analyze the results of randomized trials, yet ANOVA does not provide an estimate for the difference between groups, the key variable of interest in a randomized trial. Although the use of ANOVA is frequently justified on the grounds that a trial incorporates more than two groups, the hypothesis tested by ANOVA for these trials--"Are all groups equivalent?"--is often scientifically uninteresting. Regression methods are not only applicable to trials with many groups, but can be designed to address specific questions arising from the study design. ANOVA is also frequently used for trials with repeated measures, but the consequent reporting of "group effects," "time effects," and "time-by-group interactions" is a distraction from statistics of clinical and scientific value. Given that ANOVA is easily misapplied in the analysis of randomized trials, alternative approaches such as regression methods should be considered in preference.

Effect of Vehicle Operation, Weight, and Accessory Use on Emissions from a Modern Heavy-Duty Diesel Truck

The objective was to determine the effect of several variables—vehicle operation, weight, and accessory use—on emissions production during common on-road heavy-duty vehicle operations. Oxides of nitrogen (NOX), hydrocarbon, and carbon monoxide emissions from a heavy-duty diesel tractor equipped with a 1999 engine were measured continuously during on-road tests. The vehicle was operated at predetermined steady-state modes of 25, 55, and 65 mph as well as full-throttle accelerations from 0 to 25 mph and 0 to 55 mph and decelerations from 65 to 0 mph. Vehicle weight (payload) and accessory use (air-conditioning) were varied. In general, increases in gross vehicle weight from 52,000 Ib to 80,000 Ib resulted in approximately 40% or greater increases in NOX grams per mile (g/mi) emissions during the accelerations and higher-speed steady-state operations. These results were consistent with simulation model results from the National Renewable Energy Laboratory's ADVISOR model. Analysis of variance (ANOVA) and regression models were used to identify relationships between the variables and emissions. With the use of ANOVA, it was found that mode explained most of the variation in emissions and had a significant impact on all species of emissions tested. With the use of regression, a strong relationship was confirmed between steady-state modal NOX emissions per hour and horsepower ( r2 = 0.89, P <.0001). When mode and weight were added as factors in the regression model, the overall precision of NOX emissions prediction was increased and horsepower became nonsignificant.

Gallium extraction by microemulsions

In this work, the use of microemulsion in the extraction of gallium, with Bayer process, has been studied. The studied microemulsion systems were: systems I and II, with saponified coconut oil (SCO) and 4-ethyl,1-methyl,7-octyl,8-hydroxyquinoleine (Kelex-100) as extractants. The extraction essays by microemulsion were carried out by applying an experimental planning method whose microemulsion points were prepared within an experimental domain favorable to the extraction. Gallium and aluminum extraction percentages, in each point, were evaluated via a statistical treatment of the data, with the use of variance analysis and mathematical models. In system I (SCO), percentages of extraction of 85.5% for gallium and 35.4% for aluminum were achieved; in system II (Kelex-100), the yields were 100% for gallium and 99.9% for aluminum. The reextraction study with sulfuric acid presented the same behavior for both systems, with efficiency depending upon the concentration of the acid, and allowing for a selective reextraction of gallium and aluminum.

Aplicação da análise de variância na implantação do CEP

Este artigo apresenta uma aplicação da Análise de Variância (ANOVA) na identificação das fontes de variabilidade em um processo de laminação de barras de aço, utilizado em uma empresa metal-mecánica sediada no Rio Grande do Sul. A principal fonte de variabilidade observada no processo de laminação foi o tipo de aço. O estudo das possíveis fontes de variabilidade serviu de base para o estabelecimento do controle estatístico do processo (CEP), o qual é descrito neste trabalho juntamente com os respectivos estudos cie estabilidade e capacidade. Conclui-se que o uso conjunto da ANOVA e do CEP pode trazer benefícios as empresas, na medida em que a ANOVA propicia uma estratégia para o agrupamento de variáveis e para a escolha seletiva das cartas de controle a serem utilizadas.

Adaptive noise reduction by using cascaded sandglass‐type neural networks

AbstractAn adaptive noise reduction filter composed of cascaded sandglass‐type neural networks (CSNNRF) is proposed. A given number of unit sandglass‐type neural networks (SNN), each of which has a three‐layer structure and consists of the same number of neural units in the input and the output layers and a single neural unit the hidden layer, are connected in cascade. The number of unit SNNs is adaptively determined so as to be equal to a rank of covariance matrix of an original noise‐free signal (signal component). Outputs of hidden layer units in individual unit SNNs, whose variances are equivalent to eigenvalues of the covariance matrix of the observed signal, are statistically compared by use of ANOVA (analysis of variance) to estimate the rank. When a CSNNRF is composed of the number of unit SNNs equal to the rank, the observed signal is filtered without any loss of signal component while noise component is maximally reduced. It was shown by computer experiments that the rank was almost always estimated accurately in an adaptive manner, and that noise reduction from the signal was carried out optimally. © 2001 Scripta Technica, Electr Eng Jpn, 136(1): 37–46, 2001

A Cusp Catastrophe Analysis of Anxiety Levels in Pre-University Students

Nonlinear or discontinuous change was analyzed by applying a catastrophe shift model to data collected on the anxiety levels of Year 12 students immediately before and immediately after they received offers of university places. Students' anxiety levels were expected to be subject to rapid change from prearrival of university offers to postarrival of offers. This process is described, in catastrophe shift terms, as discontinuous or nonlinear change and can indicate a change in state rather than a linear change in degree. Significant differences were revealed in anxiety levels from prearrival of offers to postarrival of offers for Preference Groups 1, 2, and 3. Bimodality was also revealed, using analysis of variance (ANOVA); however, analysis using cubic regression indicated that only Preference Groups 1 and 2 demonstrated significant nonlinear change. These findings suggest that the use of cubic regression analysis to identify nonlinear change may reveal more complex changes than is indicated by the use of ANOVA alone.

Robustness of the ANOVA and Tukey-Kramer statistical tests

Analysis of variance (ANOVA) allows one to compare the means of μ 1, μ 2,…, μ m of m populations. For a randomized block single-factor design of experiments with m treatments, the analyst uses ANOVA to test the null hypothesis H 0 : { μ 1 = μ 2 = … = μ m }. If H 0 is rejected, the Tukey-Kramer procedure may be used to determine which pairs of means have statistically significant differences. Unfortunately, ANOVA and the Tukey-Kramer procedures both depend upon the use of data from normal populations. Departure from normality may cause errors. These errors cannot be determined analytically; however, they can be estimated via simulation. This paper reports on the use of computer simulation to estimate the errors that attend the use of ANOVA with Tukey-Kramer to test for differences of population means.

The misuse of analysis of variance to detect synergy in combination drug studies

Drug combination studies often examine the possibility of synergy between drugs. Synergy is defined as an effect of a combination of drugs greater than that expected from the effects of the drugs given individually. One technique used by several investigators is the use of analysis of variance (ANOVA) to determine synergy. In this discussion, the argument is made that due to the pharmacology of drug combination studies the conditions necessary to support the use of ANOVA to detect synergy are typically not met. Therefore, the ANOVA technique is invalid for these drug combination studies.