Descriptive Statistics and Normality Tests for Statistical Data
Descriptive Statistics and Normality Tests for Statistical Data
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DOI：
10.4103/aca.aca_157_18
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发表时间：
2019-01-01
影响因子：
0.9
通讯作者：
Keshri, Amit
中科院分区：
文献类型：
--
作者：
Mishra, Prabhaker;Pandey, Chandra M.;Keshri, Amit
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的简单摘要。集中趋势和分散的措施被用来描述定量数据。对于连续数据，正态性检验是确定集中趋势测度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，参数检验或非参数方法用于组间比较。数据正态性检验有不同的方法，包括数值法和直观法，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概括性度量和方法。
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.