{"title":"P 值的含义","authors":"Umar Hussain, Farhad Ali","doi":"10.52206/jsmc.2023.13.4.839","DOIUrl":null,"url":null,"abstract":"In medical and dental research, we are usually interested in understanding the real effect of two or more interventions (such as drugs or surgeries) on an outcome (such as signs and symptoms of a disease). To test such effects, we typically establish two hypotheses: the null hypothesis and the alternative hypothesis. In the null hypothesis, the researcher assumes that there is no difference between the two interventions on the outcome, while the alternative hypothesis assumes that a difference exists. We collect, clean, and analyze data using an appropriate statistical test. The test produces a p-value, which ranges from 0 to 1. The researcher sets a significance level (usually p ≤ 0.05).A small p-value (typically ≤ 0.05) suggests there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis. Conversely, a larger p-value indicates a lack of evidence to reject the null hypothesis.","PeriodicalId":326561,"journal":{"name":"Journal of Saidu Medical College, Swat","volume":" 51","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Meaning of P-value\",\"authors\":\"Umar Hussain, Farhad Ali\",\"doi\":\"10.52206/jsmc.2023.13.4.839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In medical and dental research, we are usually interested in understanding the real effect of two or more interventions (such as drugs or surgeries) on an outcome (such as signs and symptoms of a disease). To test such effects, we typically establish two hypotheses: the null hypothesis and the alternative hypothesis. In the null hypothesis, the researcher assumes that there is no difference between the two interventions on the outcome, while the alternative hypothesis assumes that a difference exists. We collect, clean, and analyze data using an appropriate statistical test. The test produces a p-value, which ranges from 0 to 1. The researcher sets a significance level (usually p ≤ 0.05).A small p-value (typically ≤ 0.05) suggests there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis. Conversely, a larger p-value indicates a lack of evidence to reject the null hypothesis.\",\"PeriodicalId\":326561,\"journal\":{\"name\":\"Journal of Saidu Medical College, Swat\",\"volume\":\" 51\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Saidu Medical College, Swat\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52206/jsmc.2023.13.4.839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Saidu Medical College, Swat","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52206/jsmc.2023.13.4.839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
在医学和牙科研究中,我们通常希望了解两种或两种以上干预措施(如药物或手术)对结果(如疾病的体征和症状)的实际影响。为了检验这种效果,我们通常会提出两个假设:零假设和备择假设。在零假设中,研究人员假定两种干预措施对结果没有差异,而在备择假设中则假定存在差异。我们使用适当的统计检验来收集、清理和分析数据。研究人员设定一个显著性水平(通常 p ≤ 0.05)。小的 p 值(通常 ≤ 0.05)表明有足够的证据来拒绝零假设,支持备择假设。相反,如果 p 值较大,则表明缺乏拒绝零假设的证据。
In medical and dental research, we are usually interested in understanding the real effect of two or more interventions (such as drugs or surgeries) on an outcome (such as signs and symptoms of a disease). To test such effects, we typically establish two hypotheses: the null hypothesis and the alternative hypothesis. In the null hypothesis, the researcher assumes that there is no difference between the two interventions on the outcome, while the alternative hypothesis assumes that a difference exists. We collect, clean, and analyze data using an appropriate statistical test. The test produces a p-value, which ranges from 0 to 1. The researcher sets a significance level (usually p ≤ 0.05).A small p-value (typically ≤ 0.05) suggests there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis. Conversely, a larger p-value indicates a lack of evidence to reject the null hypothesis.