List of Articles Statistical Analysis

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  1 - Statistical Analysis and Comparison of the Performance of Meta-Heuristic Methods Based on their Powerfulness and Effectiveness
  Mehrdad Rohani Hassan Farsi Seyed Hamid Zahiri
  10.52547/jist.16067.10.37.49
  In this paper, the performance of meta-heuristic algorithms is compared using statistical analysis based on new criteria (powerfulness and effectiveness). Due to the large number of meta-heuristic methods reported so far, choosing one of them by researchers has always b More

  In this paper, the performance of meta-heuristic algorithms is compared using statistical analysis based on new criteria (powerfulness and effectiveness). Due to the large number of meta-heuristic methods reported so far, choosing one of them by researchers has always been challenging. In fact, the user does not know which of these methods are able to solve his complex problem. In this paper, in order to compare the performance of several methods from different categories of meta-heuristic methods new criteria are proposed. In fact, by using these criteria, the user is able to choose an effective method for his problem. For this reason, statistical analysis is conducted on each of these methods to clarify the application of each of these methods for the users. Also, powerfulness and effectiveness criteria are defined to compare the performance of the meta-heuristic methods to introduce suitable substrate and suitable quantitative parameters for this purpose. The results of these criteria clearly show the ability of each method for different applications and problems. Manuscript profile
• Open Access Article
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  2 - Data Analyses in Veterinary Research & Practice
  Negin Esfandiary MohammadArad zandieh
  https://doi.org/10.61186/eltiamj.10.2.4
  Researchers can interpret and analyze livestock problems and diseases by using data obtained from different characteristics of animals and their environment. The pivotal role of statistical analysis of data in the field of veterinary research & practice is inevitable. I More

  Researchers can interpret and analyze livestock problems and diseases by using data obtained from different characteristics of animals and their environment. The pivotal role of statistical analysis of data in the field of veterinary research & practice is inevitable. In this review article, shedding light on its significance in unraveling complex patterns and drawing reliable conclusions from diverse datasets. The veterinary domain, characterized by a spectrum of species and inherent biological variability, necessitates robust statistical methodologies to discern meaningful insights. In order to make inferences about disease causation or a researcher's hypothesis, data must be categorized and the goal is to decide whether the groups are statistically different or not. Finally, using a suitable statistical test, the research hypothesis is rejected or accepted, and finally the necessary interpretations are made. The researcher can decide what data should be collected and how. In practice, in this case, the researcher's hands are open and they can make the best possible decision, but often prospective data collection is costly and time-consuming. Another mode is retrospective research, which is often based on data collected by veterinarians from slaughterhouses, laboratories, clinics, inoculation centers, etc. or from other organizations and institutions. The article explores a range of statistical techniques applied in veterinary research and practice, including data normalization, hypothesis test, parametric and non-parametric test, regression and coefficient test, and validity in veterinary medicine. These futures has shedding light on animal interactions and patterns. Ultimately, this review article serves as a comprehensive guide for researchers and practitioners in veterinary science, offering insights into the nuanced application of statistical analyses. By navigating the complexities of veterinary data, it aims to empower the scientific community to leverage statistical tools effectively, ultimately advancing the quality and reliability of research in veterinary medicine. Manuscript profile