Mishra Prabhaker, Pandey Chandra Mani, Singh Uttam, Keshri Amit, Sabaretnam Mayilvaganan
Department of Biostatistics and Health Informatics, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Department of Neuro-otology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Ann Card Anaesth. 2019 Jul-Sep;22(3):297-301. doi: 10.4103/aca.ACA_248_18.
In biostatistics, for each of the specific situation, statistical methods are available for analysis and interpretation of the data. To select the appropriate statistical method, one need to know the assumption and conditions of the statistical methods, so that proper statistical method can be selected for data analysis. Two main statistical methods are used in data analysis: descriptive statistics, which summarizes data using indexes such as mean and median and another is inferential statistics, which draw conclusions from data using statistical tests such as student's t-test. Selection of appropriate statistical method depends on the following three things: Aim and objective of the study, Type and distribution of the data used, and Nature of the observations (paired/unpaired). All type of statistical methods that are used to compare the means are called parametric while statistical methods used to compare other than means (ex-median/mean ranks/proportions) are called nonparametric methods. In the present article, we have discussed the parametric and non-parametric methods, their assumptions, and how to select appropriate statistical methods for analysis and interpretation of the biomedical data.
在生物统计学中,针对每种具体情况,都有可供数据分析和解释的统计方法。为选择合适的统计方法,需要了解这些统计方法的假设和条件,以便能为数据分析选择恰当的统计方法。数据分析中使用两种主要的统计方法:描述性统计,它使用均值和中位数等指标汇总数据;另一种是推断性统计,它使用诸如学生t检验等统计检验从数据中得出结论。选择合适的统计方法取决于以下三点:研究的目的和目标、所使用数据的类型和分布,以及观察结果的性质(配对/非配对)。所有用于比较均值的统计方法都称为参数方法,而用于比较均值以外的其他数据(如中位数/平均秩次/比例)的统计方法称为非参数方法。在本文中,我们讨论了参数方法和非参数方法、它们的假设,以及如何选择合适的统计方法来分析和解释生物医学数据。