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PhD Students and the Most Frequent Mistakes During Data Interpretation by Statistical Analysis Software

机译:统计分析软件数据解释期间的博士生和最常见的错误

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摘要

Correct choice and administration of a statistical test are absolutely essential for meaningful interpretation of research data, yet mistakes are still frequent and could be easily found in published scientific papers or PhD theses. The aim of this study was to analyze mistakes made by PhD students in statistical analysis of data collected during research within the framework of their thesis. PhD students frequently use Excel and SPSS for data processing, while SAS, Stata and R are also available. The study was designed as cross-sectional analysis of random sample (n=15) of PhD theses in pre-approval stage at Faculty of Medical Sciences, University ofKragujevac, Serbia, hi total 14 (93%) theses had at least one mistake. The most frequent mistakes were as the following: insufficient statistical power due to small sample size, inappropriate presentation of results at tables and graphs, andinappropriate choice of statistical tests. In order to improve the situation, training courses in statistics during PhD studies should be re-evaluatcd and improved in regard to relevance, delivery methods and motivating potential, and mentors should invest more effort to review the data and guide students through statistical analysis.
机译:纠正统计测试的正确选择和管理对于对研究数据的有意义解释绝对是必不可少的,但错误仍然是频繁的,并且可以在公布的科学论文或博士学位中找到。本研究的目的是分析博士学生博士学位在论文框架内收集的数据统计分析的统计分析。博士生经常使用Excel和SPS进行数据处理,而SAS,STATA和R也可用。该研究被设计为对塞尔维亚大学在医学院大学的预审阶段的随机样品(n = 15)的横截面分析,HI总数为14(93%),至少有一个错误。最常见的错误如下:由于小样本大小,统计功率不足,表格和图表中的结果不恰当地呈现,而且统计测试的选择。为了改善情况,博士学位研究期间的统计培训课程应重新评估,并在相关性,交付方法和激励潜力方面改善,并通过统计分析来投入更多努力审查数据和指导学生。

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  • 来源
    《ICIMTH》|2019年|xv 404 p. :|共5页
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    Izet MASIC;

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  • 中图分类 R-058;
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