ArticleJournal of animal science2021
Assessing the statistical training in animal science graduate programs in the United States: survey on statistical training.
Article in Journal of animal science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Teaching students to R3eason, not merely to solve problem sets: The role of philosophy and visual data communication in accessible data science education.PLoS computational biology · 2023Article
- ASAS-NANP symposium: mathematical modeling in animal nutrition-Making sense of big data and machine learning: how open-source code can advance training of animal scientists.Journal of animal science · 2023Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Statistical analysis of data and understanding of experimental design are critical skills needed by animal science graduate students (ASGS). These skills are even more valuable with the increased development of high-throughput technologies. The objective of this study was to evaluate the perceived statistical training of U.S. ASGS. A survey with 38 questions was shared across U.S. universities, and 416 eligible ASGS from 43 universities participated in this study. The survey included questions on the demographics and overall training, graduate education on statistics, and self-assessment on statistics and career path of ASGS. Several analyses were performed: relationship between perceived received education (PRE; i.e., how ASGS evaluated their graduate education in statistics) and perceived knowledge (PK; i.e., how ASGS evaluated their knowledge in statistics from their education); ranking of statistical topics based on PRE, PK, and confidence in performing statistical analyses (CPSA); cluster analysis of statistical topics for PRE, PK, and CPSA; and factors (demographic, overall training, interest in statistics, and field of study) associated with the overall scores (OS) for PRE, PK, and CPSA. Students had greater (P < 0.05) PRE than PK for most of the statistical topics included in this study. The moderate to high repeatability of answers within statistical topics indicates substantial correlations in ASGS answers between PRE and PK. The cluster analysis resulted in distinct groups of "Traditional" and "Nontraditional" statistical topics. ASGS showed lower (P < 0.05) scores of PRE, PK, and CPSA in "Nontraditional" compared with "Traditional" statistical methods. Several factors were associated (P < 0.05) with the OS of PRE, PK, and CSPA. In general, factors related to greater training and interest in statistics of ASGS were associated with greater OS, such as taking more credits in statistics courses, having additional training in statistics outside the classroom, knowing more than one statistics software, and more. This study provided comprehensive information on the perceived level of education, knowledge, and confidence in statistics in ASGS in the United States. Although objective measurements of their training in statistics are needed, the current study suggests that ASGS have limited statistical training on topics of major importance for the current and future trends of data-driven research in animal sciences.
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