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testing for statistically significant differences between two group means is one of the most common requirements in psychological research, for example, after an experiment has been conducted. While the classical t-test is probably the most popular approach, its deficiencies under violated assumptions have been acknowledged, and various alternative tests have been developed. In this research paper, five widely available methods are compared to investigate the coverage of the generated 95\% confidence intervals. We utilize the coverage of confidence intervals as it corresponds to nominal type-I-error rates (Alpha), yet is more adequate since confidence intervals are preferred in contrast to p-values, which often facilitate binary conclusions. The approaches tested are the classical t-test, Welch’s t-test, OLS regressions with robust standard errors, and two flavors of bootstrapping (normal and bias-corrected). Three different outcome distributions are generated (normal, uniform, skewed), and 75,000 simulations with a wide range of sample sizes (15 to 200 per group) and standard deviations are conducted for each. The results outline that Welch’s t-test and the regression approach perform best. The bootstrap approaches tend to consistent undercoverage. The regular t-test produces larger deviations when its assumptions, especially the equality of variances, are violated. When distributions are skewed, all approaches result in undercoverage.

Abstract Background Basil is one of the most famous herbs, which has broad usage as a fresh vegetable and therapeutic and pharmaceutical services. The main abiotic stress limiting basil production globally is drought. As a result, appropriate drought screening-which effectively separates high-yielding but drought-sensitive genotypes from drought-tolerant genotypes-is necessary for the optimal selection of high-yielding basil cultivars under drought stress conditions. So, a split plot experiment with three replications based on a completely randomized design were carried out in a pot under field conditions for this investigation. Water levels (full irrigation or control, moderate stress, and severe stress) were assigned as main plots, while 22 basil accessions were given as sub-plots. In this study, leaf yield as well as physio-biochemical traits had measured on accessions. Results Our results revealed large variation in yield, essential oil (%), protein, proline, chlorophyll, total phenol and flavonoids traits across the 22 accessions. The percentage of leaf yield reduction in moderate drought stress than normal conditions showed that G1 (−6.5%), G17 (−7.05%), G20 (−9.01%), and G12 (−10.9%) accessions had the least changes, respectively. Although in severe drought stress than normal conditions, the G1 (−32.01%), G12 (−33.12%), G4 (−33.24%), G7 (−34.11%), and G17 (−34.93%) accessions had the least amount of change in plant leaf yield, respectively. Furthermore, the highest yield reduction occurred in moderate and severe stress conditions in G18 (−25.36%) and G8 (−42.98%) accessions, respectively. Cluster analysis based on the ward method in both conditions (moderate and severe drought conditions) placed the accessions in three groups, and accessions were identified as tolerant, whose average traits in that group were higher than the total average. The principal component analysis also showed that in moderate drought conditions, the first two components explained about 95.28% of the total variation, while in severe drought conditions, these two components explained about 96.37% of the total variation. Conclusions The different multivariate analyses (cluster analysis, PCA, mean comparison) were used to identify tolerant and sensitive accessions based on all traits. The accessions G3, G4, G6, and G7 were found to be tolerant to stress, while G10, G15, G16, and G20 were found to be sensitive to drought. These accessions are a useful step in producing drought-tolerant, high-yielding accessions and can be utilized in breeding programs for basil.

Introduction: Considering the production of new silkworm hybrids by prominent countries in the sericulture industry such as China and the import of these hybrids to the country in recent years, it is necessary to update these evaluations so that correct decisions can be made to choose the most suitable type of hybrid in terms of functional traits. Therefore, such comparisons are done annually and the results are sent to the Iran Sericultural Corporation- Silk Worm Research Center as an executive body for final decision. The present study aimed to investigate the performance of eight Chinese commercial silkworm hybrids, including Suju×Minghu (S×M), Minghu×Suju (M×S), Baiyue×Qiufeng (B×Q), Qiufeng×Baiyue (Q×B), BaiyueB×QiufengA (BB×QA), QiufengA×BaiyueB (QA×BB), 874×873, and 874×873. Hybrids 872×871 and 872×871 also were among the studied hybrids, but due to the decrease in the performance of cocoon-related traits compared to other hybrids that had a big difference in terms of the obtained values, they were removed and excluded from the final analysis. Materials and methods: The desired hybrids for 14 traits including best cocoons weight produced per 26,000 larvae (BCW), total cocoons weight produced per 26,000 larvae (TCW), number of cocoons per liter (NCPL), weight of cocoons per liter (WCPL), percentage of pupa viability (PPV), mean weight of a cocoon (MWC), mean weight of a cocoon shell (MWCS), mean of cocoon shell percentage (MCSP), mean weight of a male cocoon (MWMC), mean weight of a male cocoon shell (MWMCS), mean of male cocoon shell percentage (MMCSP), mean weight of a female cocoon (MWFC), mean weight of a female cocoon shell (MWFCS), and mean of female cocoon shell percentage (MFCSP) were reared in the spring of 2022 after hatching and according to standard methods and under the same conditions in Iran Silk Research Center and their performance was recorded. Each silkworm hybrid was reared in three replications of 200 larvae (total number of observations including 600 records per hybrid for all traits) in a completely randomized design. The analysis of the obtained data was done by SAS software by using the procedure of generalized linear model (GLM), and the average performance of the traits was compared to each other using Tukey's range test at the probability level of P<0.05. Results and discussion: The results of the analysis of variance for the studied traits showed that the effect of the hybrid type for most of the studied traits including best cocoons weight produced per 26,000 larvae (BCW), total cocoons weight produced per 26,000 larvae (TCW), number of cocoons per liter (NCPL), the weight of cocoons per liter (WCPL), mean weight of a cocoon (MWC), mean weight of a cocoon shell (MWCS), mean of cocoon shell percentage (MCSP), mean weight of a male cocoon (MWMC), mean weight of a male cocoon shell (MWMCS), mean of male cocoon shell percentage (MMCSP), mean weight of a female cocoon (MWFC), mean weight of a female cocoon shell (MWFCS) and mean of female cocoon shell percentage (MFCSP) was significant (P<0.05). In the meantime, only traits of the percentage of pupa viability (PPV) as the most important index related to survival and the mean of male cocoon shell percentage (MMCSP) were not affected by the hybrid type (P<0.05). The average performance of the hybrids showed a significant difference (P<0.05) for all the traits except for the percentage of pupa viability (PPV) and the mean of cocoon shell percentage (MCSP). The BB×QA hybrid showed a higher performance than other hybrids for six traits including the best cocoons weight produced per 26,000 larvae (BCW), the total cocoons weight produced per 26,000 larvae (TCW), the weight of cocoons per liter (WCPL), the mean weight of a cocoon (MWC), the mean weight of a male cocoon (MWMC), and the mean weight of a female cocoon (MWFC) (P<0.01). Also, the M×S hybrid showed a higher performance than other hybrids for the five traits of the mean weight of a cocoon shell (MWCS), mean of cocoon shell percentage (MCSP), mean weight of a male cocoon shell (MWMCS), mean weight of a female cocoon shell (MWFCS), and the mean of female cocoon shell percentage (MFCSP) (P<0.05). In addition, the M×S hybrid showed the lowest value compared to other hybrids for the number of cocoons per liter (NCPL), which the lower values of this trait are preferred (P<0.01). Conclusions: Based on the results of the present research, the priority of importing and rearing silkworm eggs in 2023 is suggested for BB×QA and M×S hybrids. Although the performance of these two hybrids with other hybrids, except for the 874×873 and 874×873 hybrids, is not significant in most of the examined traits, they can still be considered as next-import priorities. [ABSTRACT FROM AUTHOR]

Background: Basil is one of the most famous herbs, which has broad usage as a fresh vegetable and therapeutic and pharmaceutical services. The main abiotic stress limiting basil production globally is drought. As a result, appropriate drought screening-which effectively separates high-yielding but drought-sensitive genotypes from drought-tolerant genotypes-is necessary for the optimal selection of high-yielding basil cultivars under drought stress conditions. So, a split plot experiment with three replications based on a completely randomized design were carried out in a pot under field conditions for this investigation. Water levels (full irrigation or control, moderate stress, and severe stress) were assigned as main plots, while 22 basil accessions were given as sub-plots. In this study, leaf yield as well as physio-biochemical traits had measured on accessions. Results: Our results revealed large variation in yield, essential oil (%), protein, proline, chlorophyll, total phenol and flavonoids traits across the 22 accessions. The percentage of leaf yield reduction in moderate drought stress than normal conditions showed that G1 (−6.5%), G17 (−7.05%), G20 (−9.01%), and G12 (−10.9%) accessions had the least changes, respectively. Although in severe drought stress than normal conditions, the G1 (−32.01%), G12 (−33.12%), G4 (−33.24%), G7 (−34.11%), and G17 (−34.93%) accessions had the least amount of change in plant leaf yield, respectively. Furthermore, the highest yield reduction occurred in moderate and severe stress conditions in G18 (−25.36%) and G8 (−42.98%) accessions, respectively. Cluster analysis based on the ward method in both conditions (moderate and severe drought conditions) placed the accessions in three groups, and accessions were identified as tolerant, whose average traits in that group were higher than the total average. The principal component analysis also showed that in moderate drought conditions, the first two components explained about 95.28% of the total variation, while in severe drought conditions, these two components explained about 96.37% of the total variation. Conclusions: The different multivariate analyses (cluster analysis, PCA, mean comparison) were used to identify tolerant and sensitive accessions based on all traits. The accessions G3, G4, G6, and G7 were found to be tolerant to stress, while G10, G15, G16, and G20 were found to be sensitive to drought. These accessions are a useful step in producing drought-tolerant, high-yielding accessions and can be utilized in breeding programs for basil. [ABSTRACT FROM AUTHOR]

Accurate investigation of kinetics and development of high-precision seed drying models will help better studying the drying process by identifying effective parameters. Present study investigates the application of cold plasma (CP), as a pretreatment process, in air drying of canola seeds. This may bring about some complication into the drying kinetics investigation. Canola seeds with an initial moisture content of 27.5±1% (dry basis) were exposed to CP for 0, 15, 30, and 60 s prior to fluidization by air at temperatures of 40, 50 and 60 °C in a pilot scale fluidized bed heated by a solar panel. The results showed a decreasing trend in drying time from 40 to 60 oC. The shortest drying time corresponds to samples dried at 60 oC with no CP pretreatment. The longest period however occurred for samples dried at 40 oC with 60 s of CP pretreatment. The greatest effect of CP on reducing the drying time was observed at temperatures of 40 and 50 °C at the CP exposure time of 15 and 60 s, respectively. A reasonably accurate study of drying kinetics was accomplished using the superposition method. Accordingly, using experimental data, curves correspond to different drying conditions were plotted and in two steps these were shifted to a reference curve to acquire a final drying curve. The curve then was fitted to a second-order equation, and was validated using the experimental data. The correlation coefficients, mean square error and mean absolute error were 0.99, 0.03, and 0.023, respectively.

Accurate investigation of kinetics and development of high-precision seed drying models will help better studying the drying process by identifying effective parameters. Present study investigates the application of cold plasma (CP), as a pretreatment process, in air drying of canola seeds. This may bring about some complication into the drying kinetics investigation. Canola seeds with an initial moisture content of 27.5±1% (dry basis) were exposed to CP for 0, 15, 30, and 60 s prior to fluidization by air at temperatures of 40, 50 and 60°C in a pilot scale fluidized bed heated by a solar panel. The results showed a decreasing trend in drying time from 40 to 60°C. The shortest drying time corresponds to samples dried at 60°C with no CP pretreatment. The longest period however occurred for samples dried at 40°C with 60 s of CP pretreatment. The greatest effect of CP on reducing the drying time was observed at temperatures of 40 and 50°C at the CP exposure time of 15 and 60 s, respectively. A reasonably accurate study of drying kinetics was accomplished using the superposition method. Accordingly, using experimental data, curves correspond to different drying conditions were plotted and in two steps these were shifted to a reference curve to acquire a final drying curve. The curve then was fitted to a second-order equation, and was validated using the experimental data. The correlation coefficients, mean square error and mean absolute error were 0.99, 0.03, and 0.023, respectively. [ABSTRACT FROM AUTHOR]

In many disciplines of the social sciences, comparisons between a group mean and the total mean is a common but also challenging task. As one solution to this statistical testing problem, we propose using linear regression with weighted effect coding. For random samples, this procedure is straightforward and easy to implement by means of standard statistical software. However, for complex or clustered samples with imputed or weighted data, which are common in survey analyses, there is a lack of easy-to-use software solutions. In this paper, we discuss scenarios that are commonly encountered in the social sciences such as heterogeneous variances, weighted samples, and clustered samples, and we describe how group means can be compared to the total mean in these situations. We introduce the R package eatRep, which is a front end that makes the presented methods easily accessible for researchers. Two empirical examples, one using survey data (MIDUS 1) and the other using large-scale assessment data (PISA 2015), are given for illustration. Annotated R code to run group to total mean comparisons is provided. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has changed the consumption habits of tourists to benefit sustainable destinations that are not overcrowded, such as rural tourism destinations. However, the periods of compulsory lockdown have had devastating effects on tourism businesses operating in rural areas and have even jeopardised their economic viability. The aim of this article is to quantify in relative terms the effects that the period of compulsory lockdown in a markedly tourist country, such as Spain, between March and May 2020 has had on rural accommodation in one of the most rural provinces of Spain (Cáceres). Based on a random sample of 225 rural accommodation establishments and the consideration of various factors, statistical techniques of comparison of means and proportions were used to detect differences in the intensity of the effects of the compulsory lockdown on the economic-financial management, bookings, facilities, and input of rural accommodation establishments in the province. The results obtained show that the economic, labour, and management effects of the COVID-19 pandemic on rural tourism businesses in the province of Cáceres have been very substantial. In particular, the businesses with the highest level of tourist services on supply, i.e., those that, in addition to accommodation, also offer other tourist activities, have been the most affected. In view of this situation, urgent emergency measures have been put in place at a provincial level to alleviate the economic loss and the destruction of jobs caused by this pandemic. [ABSTRACT FROM AUTHOR]

Extreme response style (ERS) is prevalent in survey research using rating scales. It may cause biased results in group comparisons. This research conducted two sets of simulation studies to explore the magnitude of the ERS impact on mean comparisons between two independent samples. Data were generated from a multidimensional nominal response model. Study 1 examined the influence of ERS on the estimate of group differences in the variable of interest. The results indicated that ERS led to biased estimates, especially when these groups differed significantly in ERS. The correlation between ERS and the variable of interest also moderated the ERS impact. The results were illustrated with an empirical example. Study 2 investigated the impact of ERS on the type I error and type II error in the independent t -test based on scale scores. When the variable of interest had no true difference between groups, ERS inflated the type I error rate. When the difference existed, ERS inflated the type II error rate. Two groups' true difference in ERS and the variable of interest, unequal ERS variances, the correlation between ERS and the variable of interest, and the number of items moderated the impact of ERS on type I and II error rates. The implications for practices and further research are discussed. [ABSTRACT FROM AUTHOR]

Checking the normality assumption is necessary to decide whether a parametric or non-parametric test needs to be used. Different ways are suggested in literature to use for checking normality. Skewness and kurtosis values are one of them. However, there is no consensus which values indicated a normal distribution. Therefore, the effects of different criteria in terms of skewness values were simulated in this study. Specifically, the results of t-test and U-test are compared under different skewness values. The results showed that t-test and U-test give different results when the data showed skewness. Based on the results, using skewness values alone to decide about normality of a dataset may not be enough. Therefore, the use of non-parametric tests might be inevitable.

The COVID-19 pandemic has changed the consumption habits of tourists to benefit sustainable destinations that are not overcrowded, such as rural tourism destinations. However, the periods of compulsory lockdown have had devastating effects on tourism businesses operating in rural areas and have even jeopardised their economic viability. The aim of this article is to quantify in relative terms the effects that the period of compulsory lockdown in a markedly tourist country, such as Spain, between March and May 2020 has had on rural accommodation in one of the most rural provinces of Spain (Cáceres). Based on a random sample of 225 rural accommodation establishments and the consideration of various factors, statistical techniques of comparison of means and proportions were used to detect differences in the intensity of the effects of the compulsory lockdown on the economic-financial management, bookings, facilities, and input of rural accommodation establishments in the province. The results obtained show that the economic, labour, and management effects of the COVID-19 pandemic on rural tourism businesses in the province of Cáceres have been very substantial. In particular, the businesses with the highest level of tourist services on supply, i.e., those that, in addition to accommodation, also offer other tourist activities, have been the most affected. In view of this situation, urgent emergency measures have been put in place at a provincial level to alleviate the economic loss and the destruction of jobs caused by this pandemic.

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Soil scientists are accustomed to geostatistical methods and tools such as semivariograms and kriging for analysis of observational data. Such methods assume and exploit that observations are spatially correlated. Conversely, analysis of variance (ANOVA) of designed experiments assumes that observations from different experimental units are independent, an assumption that is justified based on randomization. It may be beneficial, however, to perform an ANOVA assuming a geostatistical covariance model. Also, it is increasingly common to have multiple observations per experimental unit. Simple ANOVA assuming independence of observations is not appropriate for such data. Instead, a linear mixed model accounting for correlation among observations made on the same plot is required for proper analysis. The purpose of this paper is to demonstrate the benefits of integrating geostatistical covariance structures and ANOVA procedures into a linear mixed modelling framework. Two examples from designed experiments are considered in detail, making a link between terminologies and jargon used in geostatistical analysis on the one hand and linear mixed modelling on the other hand. We provide code in R and SAS for both examples in two supporting companion documents. Highlights: Analysis of variance and geostatistical analysis can be joined in a mixed model.Randomization justifies the independence assumption in analysis of variance.Geostatistical models imply a correlation of errors and can improve efficiency.Lacking randomization, spatial correlation can be accounted for in a mixed model. [ABSTRACT FROM AUTHOR]

Abiotic stresses, such as drought, can induce different morphological, physiological and molecular responses in the tea plants. Since there have not been any experiments on the screening of tea genotypes in terms of drought tolerance, this study was conducted to screen the drought resistance of 14 tea clones of Iran germplasm in a randomized complete block design with three replications, separately in two stressed and non-stressed conditions at Fashalam tea station. The results of grouping the clones under normal and stress conditions and comparing their results with the results of mean comparison of the agronomic and biochemical traits showed that in all cases, clones 100, Bazri and 399 were in the group that can be identified as the drought-tolerant group. Also, the results showed that in the most cases, clones 278, 276 and 285 were placed in a group that had low values for all of the traits and could be considered as a group that are susceptible to drought stress. [ABSTRACT FROM AUTHOR]

To understand the effects of school safety practices and strategies on the school environment, researchers have consistently investigated the perceptions of students and various school personnel concerning school safety. Yet school social workers, professionals commonly employed in today’s schools to address the mental health needs of students, are often left out of the school safety discussion. Data were collected from 229 school social workers across the United States to examine: (a) school social workers’ perceptions regarding the effectiveness of various school safety strategies; (b) differences in these perceptions based on student- and school-level variables; and (c) comments from participants regarding school safety in U.S. schools. The purpose of this article is to provide timely implications concerning school safety from a unique and unstudied perspective. [ABSTRACT FROM AUTHOR]

It is common to find scientific publications with incorrect uses of the analysis of variance (ANOVA), as well as incorrect applications of tests after finding significance with the ANOVA. This paper describes the fundamentals of the ANOVA and of the tests that can be applied afterwards, and presents practical examples in food science, with the objective of showing the reader a right selection and application of such tests. [ABSTRACT FROM AUTHOR]

In business data analysis, it is well known that the comparison of several means is usually carried out by the F-test in analysis of variance under the assumption of independently collected data from all populations. This assumption, however, is likely to be violated in survey data collected from various questionnaires or time-series data. As a result, it is not justifiable or problematic to apply the traditional F-test to comparison of dependent means directly. In this article, we develop a generalized F-test for comparing population means with dependent data. Simulation studies show that the proposed test has a simple approximate null distribution and feasible finite-sample properties. Applications of the proposed test in analysis of survey data and time-series data are illustrated by two real datasets. [ABSTRACT FROM AUTHOR]

Since 2014, China's photovoltaic poverty alleviation projects (PPAPs) have developed rapidly with the strong support of the Chinese government. Nevertheless, empirical evidence on the contribution of PPAPs in improving the livelihoods of poor rural families is lacking. In order to overcome this knowledge gap, this study adopted a quasi-experimental research method based on a sample dataset of 735 poor families in Chinese rural areas before and after the project. Using five types of livelihood capital values for poor families as poverty proxy indicators, we quantified the net contribution of PPAPs to poverty reduction in rural low-income families through probability distribution comparative analysis, mean comparison analysis, and difference-in-difference regression model. Results demonstrated that the PPAPs were able to precisely target rural families requiring relief and significantly reduced poverty in China, with the net effect on livelihood capital increases for rural families determined as 31.9%. PPAPs have effectively enhanced the economic conditions and social capital of poor families, yet increases in human and natural capital performed poorly. Differences existed in the anti-poverty effect of PPAPs across the three types of solar photovoltaic resource areas. The rural socioeconomic development and access to roads were undoubtedly important factors affecting the livelihoods of rural families. • We analyzed the role of solar PV to livelihood improvements in rural China. • We quantified the poverty reduction effect of solar PV poverty alleviation. • The poverty alleviation effect of solar PV projects has regional disparities. • The formulation of a long-term development mechanism of PV poverty alleviation. [ABSTRACT FROM AUTHOR]

Large-scale land deals have attracted considerable attention for various reasons, including their implications for local livelihoods. While some view the phenomena as a development opportunity, encompassing improvement in the livelihoods of local people, others argue that it is an impoverishing scheme. Ethiopia ranks among the top in terms of the size of land leased out over the last decade. Land is a major resource of state control and investment in Ethiopia. As the foundation of their livelihoods and identity, it is simultaneously a vital resource for the local people. Highlighting the importance of land for local livelihoods and state-society relations and employing a political-ecological approach, this paper analyzes the outcomes of two land lease cases for the local people in Bakko Tibbe district of Oromia, Ethiopia. The findings show that the land leases induced a significant decline in local people's access to land, resulting in a significant reduction in crop production and livestock husbandry. The land leases also dismantled longstanding land-based social relations in both production systems. Based on empirical evidence from specific localities and contextualizing the local livelihood dynamics within broader political-economic conditions, this study contributes to the ongoing debate on livelihood impacts of global land deals. [ABSTRACT FROM AUTHOR]

• Teacher job satisfaction (TJS) was compared across 38 countries and economies. • An alignment optimization approach was used for mean comparisons of TJS. • Austria, Chile, Spain, Canada, and Argentina formed the top countries with high TJS. • Bulgaria, England, Portugal, Saudi A., and Malta formed the least ranked countries. • Our findings provide potential cues to policymakers for the TJS improvement. The purpose of this study is to compare latent means of job satisfaction across participating countries in the 2018 Teaching and Learning International Survey. The mean comparison of this nature is sparse in the literature due to lack of cross-cultural construct validity of job satisfaction scales. We applied an alignment approach that can optimize this construct validity to compare the latent mean of 153,682 teachers across 48 countries. We found that Austria, Chile, Spain, Canada, and Argentina form the top countries with highly job-satisfied teachers while the least job-satisfied teachers are from Bulgaria, England, Portugal, Saudi Arabia, and Malta. Our findings provide potential cues to policymakers/education stakeholders on which country to emulate such that teacher job satisfaction can be improved. [ABSTRACT FROM AUTHOR]

After the Fukushima Daiichi nuclear accident of 2011, interest regarding radiation safety in everyday life has increased considerably. This study investigates the general public's current level of awareness of six warning pictograms in regard to medical and natural radiation safety utilized under ISO 7010, as per Korea industrial regulations. Namely, it tests whether survey respondents can recognize pictograms related to radiation safety according to their purpose, as their inability to do so poses a serious safety problem. The empirical analysis results regarding the awareness levels for radiation safety pictograms are as follows. First, 63.3% of the respondents were unable to correctly identify the pictograms; that is, their level of understandings of the six pictograms related to everyday radiation were low. Second, the mean score for the correct responses to the question of what the six pictograms indicated in relation to everyday radiation safety was also relatively low, with a mean score of 2.79 and a standard deviation of 1.447. The primary reasons for the low awareness and understanding levels were identified to be insufficient education related to radiation safety in schools. Additionally, it is necessary to revise and rectify current warning pictograms established by the Korea Industrial Standards and ISO 7010. This study is thus significant in that it identifies the level of understanding of the pictograms and suggests the need for improvement as a diversified effort toward improving everyday radiation safety.