{"id":23007,"date":"2024-04-03T09:27:30","date_gmt":"2024-04-03T09:27:30","guid":{"rendered":"https:\/\/web.socsc.hku.hk\/event\/methods-hub-seminar-series-should-we-abolish-statistical-significance-replication-problems-in-scientific-research-and-the-role-of-statistics\/"},"modified":"2024-04-03T09:27:30","modified_gmt":"2024-04-03T09:27:30","slug":"methods-hub-seminar-series-should-we-abolish-statistical-significance-replication-problems-in-scientific-research-and-the-role-of-statistics","status":"publish","type":"event","link":"https:\/\/web.socsc.hku.hk\/tc\/event\/methods-hub-seminar-series-should-we-abolish-statistical-significance-replication-problems-in-scientific-research-and-the-role-of-statistics\/","title":{"rendered":"Methods Hub Seminar Series: Should We Abolish \u201cStatistical Significance\u201d? Replication Problems in Scientific Research and the Role of Statistics"},"content":{"rendered":"<p>Many published research findings may be false. Attempts to replicate results from high-profile scientific studies too often contradict the original findings. One source of the problem is the way that statistical hypothesis tests are commonly used in contemporary research. In particular, many scientists misunderstand p-values. The \u201cp &lt; 0.05\u201d threshold was originally intended to protect researchers from over-interpreting random variation. But \u201cstatistical significance\u201d is now often wrongly perceived as indicating the scientific robustness of a finding. When a journal editor rejects a manuscript because the p-value is larger than 0.05, publication bias is the logical consequence. In this seminar, Dr Peter Martin will clarify the concepts at the heart of the debate about \u201cstatistical significance\u201d and the crisis of replication. He will illustrate common mis-uses of p-values and explain how to avoid them. He will also discuss proposed solutions to the problem, such as open science and registered research reports, as well as the idea of abandoning \u201cstatistical significance\u201d altogether.<\/p>\n","protected":false},"author":1,"template":"","event_categories":[260],"event_tag":[859,240,242,267,239,241],"related_programme":[],"class_list":["post-23007","event","type-event","status-publish","hentry","event_categories-seminar","event_tag-hkusocialsciences","event_tag-foss","event_tag-hku","event_tag-methodshub","event_tag-socialsciences","event_tag-socientist"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2 - aioseo.com -->\n\t<meta name=\"description\" content=\"Many published research findings may be false. Attempts to replicate results from high-profile scientific studies too often contradict the original findings. One source of the problem is the way that statistical hypothesis tests are commonly used in contemporary research. 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