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Assessing the statistical training in animal science graduate programs in the United States: survey on statistical training
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 s...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280918/ https://www.ncbi.nlm.nih.gov/pubmed/33738494 http://dx.doi.org/10.1093/jas/skab086 |
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author | Serão, Nick V L Petry, Amy L Sanglard, Leticia P Rossoni-Serão, Mariana C Bundy, Jennifer M |
author_facet | Serão, Nick V L Petry, Amy L Sanglard, Leticia P Rossoni-Serão, Mariana C Bundy, Jennifer M |
author_sort | Serão, Nick V L |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8280918 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82809182021-07-16 Assessing the statistical training in animal science graduate programs in the United States: survey on statistical training Serão, Nick V L Petry, Amy L Sanglard, Leticia P Rossoni-Serão, Mariana C Bundy, Jennifer M J Anim Sci Special Topic 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. Oxford University Press 2021-03-18 /pmc/articles/PMC8280918/ /pubmed/33738494 http://dx.doi.org/10.1093/jas/skab086 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Society of Animal Science. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Special Topic Serão, Nick V L Petry, Amy L Sanglard, Leticia P Rossoni-Serão, Mariana C Bundy, Jennifer M Assessing the statistical training in animal science graduate programs in the United States: survey on statistical training |
title | Assessing the statistical training in animal science graduate programs in the United States: survey on statistical training |
title_full | Assessing the statistical training in animal science graduate programs in the United States: survey on statistical training |
title_fullStr | Assessing the statistical training in animal science graduate programs in the United States: survey on statistical training |
title_full_unstemmed | Assessing the statistical training in animal science graduate programs in the United States: survey on statistical training |
title_short | Assessing the statistical training in animal science graduate programs in the United States: survey on statistical training |
title_sort | assessing the statistical training in animal science graduate programs in the united states: survey on statistical training |
topic | Special Topic |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8280918/ https://www.ncbi.nlm.nih.gov/pubmed/33738494 http://dx.doi.org/10.1093/jas/skab086 |
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