Basic principles of descriptive statistics in medical research

N. Bulanov, A. Suvorov, O. Blyuss, Daniil B. Munblit, D. Butnaru, M. Nadinskaia, A. Zaikin
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引用次数: 3

Abstract

Descriptive statistics provides tools to explore, summarize and illustrate the research data. In this tutorial we discuss two main types of data - qualitative and quantitative variables, and the most common approaches to characterize data distribution numerically and graphically. This article presents two important sets of parameters - measures of the central tendency (mean, median and mode) and variation (standard deviation, quantiles) and suggests the most suitable conditions for their application. We explain the difference between the general population and random samples, that are usually analyzed in studies. The parameters which characterize the sample (for example, measures of the central tendency) are point estimates, that can differ from the respective parameters of the general population. We introduce the concept of confidence interval - the range of values, which likely includes the true value of the parameter for the general population. All concepts and definitions are illustrated with examples, which simulate the research data.
医学研究中描述性统计的基本原理
描述性统计提供了探索、总结和说明研究数据的工具。在本教程中,我们将讨论两种主要类型的数据——定性变量和定量变量,以及用数字和图形描述数据分布的最常用方法。本文提出了两组重要的参数-集中趋势(平均值,中位数和众数)和变异(标准差,分位数)的度量,并建议了它们的最合适的应用条件。我们解释一般人群和随机样本之间的差异,这通常是在研究中分析的。表征样本特征的参数(例如,集中趋势的度量)是点估计,可能与一般总体的各自参数不同。我们引入置信区间的概念-值的范围,它可能包括一般总体参数的真实值。所有的概念和定义用实例说明,模拟研究数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
0.70
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0.00%
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