{"id":4281,"date":"2023-08-03T05:29:59","date_gmt":"2023-08-03T05:29:59","guid":{"rendered":"https:\/\/www.editage.com\/insights\/3-simple-steps-to-help-you-pick-the-right-statistical-test\/"},"modified":"2026-04-09T12:03:31","modified_gmt":"2026-04-09T06:33:31","slug":"3-simple-steps-to-help-you-pick-the-right-statistical-test","status":"publish","type":"post","link":"https:\/\/www.editage.com\/insights\/3-simple-steps-to-help-you-pick-the-right-statistical-test","title":{"rendered":"How to choose the right statistical test"},"content":{"rendered":"<p><strong>To choose the right statistical test, consider 3 aspects: your research question, your study design, and the characteristics of your data.<\/strong><\/p>\n<p><a href=\"#_Toc226626929\">Research Question<\/a><\/p>\n<p><a href=\"#_Toc226626930\">Study Design<\/a><\/p>\n<p><a href=\"#_Toc226626931\">Data Characteristics<\/a><\/p>\n<p><strong>\u00a0<\/strong><\/p>\n<p>Working with data is both exciting and challenging, isn&#8217;t it? Statistical tests are powerful tools for <a href=\"https:\/\/www.editage.com\/blog\/decoding-statistical-data-for-accurate-insights\/\">drawing meaningful conclusions<\/a> from data in biomedical research. To make sure you&#8217;re using the right one for your study, consider 3 things:<\/p>\n<h2><a name=\"_Toc226626929\"><\/a>Research Question<\/h2>\n<p>Think about your specific research question. For instance, if you want to investigate the relationship between two continuous variables, like blood pressure and heart rate in patients, you should consider using <a href=\"https:\/\/www.editage.com\/insights\/differences-between-correlation-and-regression-learn-about-different-types-of-statistical-relationships?refer=insights-search-posts\" target=\"_blank\" rel=\"noopener\">correlation<\/a> analysis. This will help you understand whether these variables are positively or negatively related as well as the strength of this relationship. Similarly, if you\u2019re interested in whether exposure to X increases the likelihood of Y disease, you\u2019d need to calculate <a href=\"https:\/\/www.editage.com\/blog\/risk-ratios-odds-ratios-and-hazard-ratios-for-biomedical-researchers\/\" target=\"_blank\" rel=\"noopener\">odds ratios<\/a> for exposed and unexposed groups.<\/p>\n<h2><a name=\"_Toc226626930\"><\/a>Study Design<\/h2>\n<p>Next, think about your <a href=\"https:\/\/www.editage.com\/blog\/types-of-experimental-research-designs\/\" target=\"_blank\" rel=\"noopener\">study design<\/a>. Are you working with two groups or multiple groups? Are you measuring variables over time in a longitudinal study? Different study designs call for specific statistical tests that are tailored to handle the nuances of your data.<\/p>\n<p>For example, suppose you&#8217;re conducting a drug trial with multiple groups of patients and measuring the effect on pain levels at different time points. In this case, a two-way <a href=\"https:\/\/www.editage.com\/insights\/4-ways-to-make-the-most-of-your-anova-uncovering-the-real-differences-between-groups?refer=insights-search-posts\" target=\"_blank\" rel=\"noopener\">ANOVA<\/a> with <a href=\"https:\/\/www.editage.com\/insights\/all-you-need-to-know-about-repeated-measures-analysis-in-5-minutes?refer=insights-search-posts\" target=\"_blank\" rel=\"noopener\">repeated measures<\/a> would be suitable. This allows you to examine both the effect of the drug (between-group factor) and the change over time (within-group factor).<\/p>\n<h2><a name=\"_Toc226626931\"><\/a>Data Characteristics<\/h2>\n<p>Before applying any test, evaluate your data&#8217;s characteristics. For example, if you&#8217;re comparing the survival rates of patients with different treatments (categorical data), a <a href=\"https:\/\/www.editage.com\/blog\/chi-square-test-types-explained-for-biomedical-researchers\/\" target=\"_blank\" rel=\"noopener\">chi-square test<\/a> would be appropriate. This test helps determine if there is a significant association between the treatment received and the survival outcome.<\/p>\n<p>Remember, understanding the distribution of your data is vital. If you&#8217;re studying the effects of a new treatment on a continuous outcome, like tumor size reduction, check if your data is normally distributed. If it is, you can use a parametric test like a <a href=\"https:\/\/www.editage.com\/insights\/whats-the-best-way-to-check-for-differences-between-groups-t-test-chi-square-test-or-anova-a-quick-and-simple-guide?refer=insights-search-posts\" target=\"_blank\" rel=\"noopener\">t-test<\/a> or a parametric <a href=\"https:\/\/www.editage.com\/blog\/what-is-regression-and-types-of-regression-for-biomedical-researchers\/\" target=\"_blank\" rel=\"noopener\">regression<\/a> model. On the other hand, if the data is not normally distributed, consider non-parametric tests like the Mann-Whitney test or Kruskal-Wallis test.<\/p>\n<p><em>Get support from an expert biostatistician in picking the right test for your study! Check out Editage&#8217;s <a href=\"https:\/\/www.editage.com\/services\/publishing-services-packs\/statistical-analysis\">Statistical Analysis &amp; Review Services<\/a>.\u00a0\u00a0\u00a0<\/em><\/p>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>To choose the right statistical test, consider 3 aspects: your research question, your study design, and the characteristics of your data. Research Question Study Design Data Characteristics \u00a0 Working with data is both exciting and challenging, isn&#8217;t it? Statistical tests are powerful tools for drawing meaningful conclusions from data in biomedical research. To make sure [&hellip;]<\/p>\n","protected":false},"author":15,"featured_media":46198,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[2420,2403],"tags":[2622,1319,2778,366],"new_categories":[],"new_tags":[],"series":[],"class_list":["post-4281","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-analysis","category-publication-support-services","tag-analysisofdata","tag-statistical-analysis","tag-statistical-analysis-and-review","tag-statistical-reporting"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How to choose the right statistical test | Editage Insights<\/title>\n<meta name=\"description\" content=\"Learn how to choose a statistical test by considering your research question, study design, and data characteristics like distribution.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.editage.com\/insights\/3-simple-steps-to-help-you-pick-the-right-statistical-test\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"3 Simple steps to help you pick the right statistical test | Editage Insights\" \/>\n<meta property=\"og:description\" content=\"This post lists 3 steps to help you choose the right statistical test for your study. 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