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统计数据的描述性统计和正态性检验。

Descriptive statistics and normality tests for statistical data.

作者信息

Mishra Prabhaker, Pandey Chandra M, Singh Uttam, Gupta Anshul, Sahu Chinmoy, Keshri Amit

机构信息

Department of Biostatistics and Health Informatics, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.

Department of Haematology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.

出版信息

Ann Card Anaesth. 2019 Jan-Mar;22(1):67-72. doi: 10.4103/aca.ACA_157_18.

Abstract

Descriptive statistics are an important part of biomedical research which is used to describe the basic features of the data in the study. They provide simple summaries about the sample and the measures. Measures of the central tendency and dispersion are used to describe the quantitative data. For the continuous data, test of the normality is an important step for deciding the measures of central tendency and statistical methods for data analysis. When our data follow normal distribution, parametric tests otherwise nonparametric methods are used to compare the groups. There are different methods used to test the normality of data, including numerical and visual methods, and each method has its own advantages and disadvantages. In the present study, we have discussed the summary measures and methods used to test the normality of the data.

摘要

描述性统计是生物医学研究的重要组成部分,用于描述研究中数据的基本特征。它们提供了关于样本和测量值的简单总结。集中趋势和离散程度的测量用于描述定量数据。对于连续数据,正态性检验是决定集中趋势测量方法和数据分析统计方法的重要步骤。当我们的数据服从正态分布时,使用参数检验,否则使用非参数方法来比较组间差异。有不同的方法用于检验数据的正态性,包括数值方法和可视化方法,每种方法都有其优缺点。在本研究中,我们讨论了用于检验数据正态性的总结测量方法和检验方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8a6/6350423/5225ede96e8f/ACA-22-67-g004.jpg

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