Influence of some anthropometric and motor parameters on triple jump

Athletics disciplines are characterized by motor movements that can be successfully applied during the educational process or through other forms of exercise, which significantly affect the development of general psychophysical abilities of individuals. Each of the disciplines of athletics acts on the development of individual abilities, but also on the general psychophysical status of man and for this reason athletics is called the "queen of sports". Athletic activities have a characteristic of participant inclusion.The values of the paper will be based on the purpose of anthropometric, basic motor and specific motor characteristics of students aged 21 years ± 6 months.A total of 70 male students, 7 anthropometric variables, 7 motor variables and 1 specific motor variable that were tested during the period of May, of the academic year, 2020/2021 were included in the research.In the basic parameters students, based on the results achieved in this anthropometric variable, are presented as a moderately homogeneous group.Although it is seen that the acquired flexibility and convexity (Skewness and Kurtosis) have a pronounced asymmetry, in the vast majority of anthropometric variables. Although it is seen that the acquired flexibility and convexity (Skewness and Kurtosis) have a pronounced asymmetry, in the vast majority of motor and criterion variables. Thus the statistically significant coefficients of the variables with the highest degree of statistical inference (p <0.01) are denoted by two asterisks. With easier statistical conclusion criterion (p <0.05) correlation coefficients. All variables have statistically significant correlation to all anthropometric, basic and criterion motor variables.

Application of tetrad testing to the evaluation of blinding strategies for ancillary supplies used in controlled clinical trials

Background/Aims: Ensuring verum and placebo cannot be visually distinguished from each other is a critical aspect of blinded controlled clinical trials. Our objective was to propose a rational approach to the visual evaluation of placebo matching candidates. Methods: Verum and placebo samples were prepared in clear clinical ancillary supplies (intravenous bags, syringes and administration lines) covered at different levels using opaque sleeves. Triangle and tetrad tests, two sensory discriminative testing methods widely used in the food industry, were applied to assess visual differences between verum and placebo. Results: Triangle and tetrad test results allowed defining the level of opaque coverage required to ensure blinding for three biological drug molecules of therapeutic interest. While the limited number of panelists did not allow a statistically sound comparison of triangle and tetrad test methodologies, tetrad test has a theoretical higher power than triangle test, meaning fewer panelists are needed to reach the same statistical conclusion. Conclusion: Tetrad test offers a rational approach to define a blinding strategy for ancillary supplies used in a controlled clinical trial.

Characterization of Extremal Unicyclic Graphs Using F-Coindex

The study of forgotten index and coindex for the molecular structures of some special chemical graphs (compounds and drugs) has proven significant in medical and pharmaceutical drug design fields by making reliable statistical conclusion about biological properties of new chemical compounds and drugs. In mathematical chemistry, finding extreme graphs with respect to topological index is an active area of research. The aim of this paper is to characterize the family of unicyclic graphs with extreme (largest and smallest) F-coindex. Moreover, the study also contains different other properties of unicyclic graphs. All these results are based upon an alternative form of F-coindex which is established with the help of special property in the graphs.

Experimental Designs in Business Research

Conducting credible and trustworthy research to inform managerial decisions is arguably the primary goal of business and management research. Research design, particularly the various types of experimental designs available, are important building blocks for advancing toward this goal. Key criteria for evaluating research studies are internal validity (the ability to demonstrate causality), statistical conclusion validity (drawing correct conclusions from data), construct validity (the extent to which a study captures the phenomenon of interest), and external validity (the generalizability of results to other contexts). Perhaps most important, internal validity depends on the research design’s ability to establish that the hypothesized cause and outcome are correlated, that variation in them occurs in the correct temporal order, and that alternative explanations of that relationship can be ruled out. Research designs vary greatly, especially in their internal validity. Generally, experiments offer the strongest causal inference, because the causal variables of interest are manipulated by the researchers, and because random assignment makes subjects comparable, such that the sources of variation in the variables of interest can be well identified. Natural experiments can exhibit similar internal validity to the extent that researchers are able to exploit exogenous events creating (quasi-)randomized interventions. When randomization is not available, quasi-experiments aim at approximating experiments by making subjects as comparable as possible based on the best available information. Finally, non-experiments, which are often the only option in business and management research, can still offer useful insights, particularly when changes in the variables of interest can be modeled by adopting longitudinal designs.

Construct Validity in Software Engineering

Empirical research aims to establish generalizable claims from data. Such claims involve concepts that often must be measured indirectly by using indicators. Construct validity is concerned with whether one can justifiably make claims at the conceptual level that are supported by results at the operational level. We report a quantitative analysis of the awareness of construct validity in the software engineering literature between 2000 and 2019 and a qualitative review of 83 articles about human-centric experiments published in five high-quality journals between 2015 and 2019. Over the two decades, the appearance in the literature of the term construct validity increased sevenfold. Some of the reviewed articles we reviewed employed various ways to ensure that the indicators span the concept in an unbiased manner. We also found articles that reuse formerly validated constructs. However, the articles disagree about how to define construct validity. Several interpret construct validity excessively by including threats to internal, external, or statistical conclusion validity. A few articles also include fundamental challenges of a study, such as cheating and misunderstandings of experiment material. The diversity of topics discussed makes us recommend a minimalist approach to construct validity. We propose seven guidelines to establish a common ground for addressing construct validity in software engineering.

Construct Validity in Software Engineering

Empirical research aims to establish generalizable claims from data. Such claims involve concepts that often must be measured indirectly by using indicators. Construct validity is concerned with whether one can justifiably make claims at the conceptual level that are supported by results at the operational level. We report a quantitative analysis of the awareness of construct validity in the software engineering literature between 2000 and 2019 and a qualitative review of 83 articles about human-centric experiments published in five high-quality journals between 2015 and 2019. Over the two decades, the appearance in the literature of the term construct validity increased sevenfold. Some of the reviewed articles we reviewed employed various ways to ensure that the indicators span the concept in an unbiased manner. We also found articles that reuse formerly validated constructs. However, the articles disagree about how to define construct validity. Several interpret construct validity excessively by including threats to internal, external, or statistical conclusion validity. A few articles also include fundamental challenges of a study, such as cheating and misunderstandings of experiment material. The diversity of topics discussed makes us recommend a minimalist approach to construct validity. We propose seven guidelines to establish a common ground for addressing construct validity in software engineering.

The Impact of Liquidity and Leverage on Profitability in Industrial Sector in Jordan

Financial leverage is linked to the funding structure in terms of the proportion of debt in the capital structure; the higher the financial leverage is, the more the company depends on debt in its financing structure. On the other hand, the lower the debt is, the more the company relies on equity funding. The company thus decides the optimal funding combination that minimizes the company's capital costs and maximizes shareholder returns.The aim of this analysis was to quantify the effect of the analysis on the profitability of the Jordanian industrial sector listed on the Amman Stock Exchange during the period (2008-2017) and on a sample of (54) industrial companies to assess the impact of leverage and liquidity. In order to evaluate the data obtained from the actual financial statements of the industrial companies listed on the Amman Stock Exchange, a descriptive and systematic methodology was used. As a result, the statistical conclusion showed that the effect of liquidity and leverage on profitability was a significant result.

CAN Algorithm: An Individual Level Approach to Identify Consequence and Norm Sensitivities and Overall Action/Inaction Preferences in Moral Decision-Making

Recently, a multinomial process tree model was developed to measure an agent’s consequence sensitivity, norm sensitivity, and generalized inaction/action preferences when making moral decisions (CNI model). However, the CNI model presupposed that an agent considers consequences—norms—generalized inaction/action preferences sequentially, which is untenable based on recent evidence. Besides, the CNI model generates parameters at the group level based on binary categorical data. Hence, the C/N/I parameters cannot be used for correlation analyses or other conventional research designs. To solve these limitations, we developed the CAN algorithm to compute norm and consequence sensitivities and overall action/inaction preferences algebraically in a parallel manner. We re-analyzed the raw data of the original CNI model to test the methodological predictions. Our results demonstrate that: (1) the C parameter is approximately equal between the CNI model and CAN algorithm; (2) the N parameter under the CNI model approximately equals N/(1 − C) under the CAN algorithm; (3) the I parameter and A parameter are reversed around 0.5 – the larger the I parameter, the more the generalized inaction versus action preference and the larger the A parameter, the more overall action versus inaction preference; (4) tests of differences in parameters between groups with the CNI model and CAN algorithm led to almost the same statistical conclusion; (5) parameters from the CAN algorithm can be used for correlational analyses and multiple comparisons, and this is an advantage over the parameters from the CNI model. The theoretical and methodological implications of our study were also discussed.

Importance of Trees Outside Forest (TOF) for immediate earthquake response

A study was carried out in Thulosirubari village of Chautara Sangachowkgadi municipality of Sindhupalchok district, Nepal to analyse the importance of TOF for immediate earthquake response and recovery. More than 80% of the households have trees in their own land with species such as Chilaune (Schima wallichii), Kutmiro (Litsea monopetala), Khote Salla (Pinus roxburghii) and Bamboo are common. Among surveyed households (134), more than 75% respondents reported that they used Schima wallichii for pillar (Khaba) to make temporary houses, whereas bamboo was used for all kind of poles (Dada/Vata/Balo) in more than 80% of temporary houses. Both Bamboo and Schima wallichii were either extracted from their own land or from neighbour's land, i.e. TOF which were easily available and collected as required. We could not draw any statistical conclusion in choice of species to construct temporary houses by wealth categories. However, we have observed that people who have sufficient and varieties of trees in own land, have selected strong and hard wood for permanent house construction whereas those who do not have choice, are limited to use any of the available tree species. People were highly aware about importance of trees to cope with disaster; however selection of species was still debatable because of limited knowledge and researches. J. Biodivers. Conserv. Bioresour. Manag. 2020, 6(1): 9-16

Measurement Schmeasurement: Questionable Measurement Practices and How to Avoid Them

In this article, we define questionable measurement practices (QMPs) as decisions researchers make that raise doubts about the validity of the measures, and ultimately the validity of study conclusions. Doubts arise for a host of reasons, including a lack of transparency, ignorance, negligence, or misrepresentation of the evidence. We describe the scope of the problem and focus on how transparency is a part of the solution. A lack of measurement transparency makes it impossible to evaluate potential threats to internal, external, statistical-conclusion, and construct validity. We demonstrate that psychology is plagued by a measurement schmeasurement attitude: QMPs are common, hide a stunning source of researcher degrees of freedom, and pose a serious threat to cumulative psychological science, but are largely ignored. We address these challenges by providing a set of questions that researchers and consumers of scientific research can consider to identify and avoid QMPs. Transparent answers to these measurement questions promote rigorous research, allow for thorough evaluations of a study’s inferences, and are necessary for meaningful replication studies.