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研究数据解读:选定的统计程序

Interpretation of research data: selected statistical procedures.

作者信息

Jackson R A

出版信息

Am J Hosp Pharm. 1980 Dec;37(12):1673-80.

PMID:7446542
Abstract

Selected statistical procedures used in the analysis of research data are presented. The relationship of significance testing to research hypotheses is explained in terms of tests of differences and correlation. Also, the differences, assumptions, and advantages and disadvantages of parametric and nonparametric statistics are discussed. With regard to each statistic presented, emphasis is placed on the hypotheses that would be tested, the kinds of data for which the statistic is appropriate, the method of calculation, and how to test for "significance." The selected statistical procedures include the Student's t-test and chi square. An explanation of the concept of correlation is provided, and several correlation coefficients are discussed, including the Pearson r, Spearman rho, Kendall's tau, the point biserial, biserial, phi coefficient, and contingency coefficient. Pharmacists must know basic statistical procedures in order to be able to effectively interpret the results of published research or to appropriately analyze data that have been collected in their own research endeavors.

摘要

介绍了研究数据分析中使用的选定统计程序。从差异检验和相关性方面解释了显著性检验与研究假设的关系。此外,还讨论了参数统计和非参数统计的差异、假设以及优缺点。对于所介绍的每种统计方法,重点在于将被检验的假设、该统计方法适用的数据类型、计算方法以及如何进行“显著性”检验。选定的统计程序包括学生t检验和卡方检验。提供了相关性概念的解释,并讨论了几种相关系数,包括皮尔逊r、斯皮尔曼rho、肯德尔tau、点二列相关、二列相关、phi系数和列联系数。药剂师必须了解基本的统计程序,以便能够有效地解释已发表研究的结果,或适当地分析他们自己研究工作中收集的数据。

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