{"id":1979,"date":"2025-01-16T13:26:55","date_gmt":"2025-01-16T12:26:55","guid":{"rendered":"https:\/\/guillaume-guerard.com\/?page_id=1979"},"modified":"2025-01-16T13:40:37","modified_gmt":"2025-01-16T12:40:37","slug":"recherche-correlationnelle","status":"publish","type":"page","link":"https:\/\/guillaume-guerard.com\/en\/cours-de-methodologie\/recherche-correlationnelle\/","title":{"rendered":"Correlational research"},"content":{"rendered":"<div data-elementor-type=\"wp-page\" data-elementor-id=\"1979\" class=\"elementor elementor-1979\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-0b60ac9 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"0b60ac9\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-f3301cb\" data-id=\"f3301cb\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-66462dd elementor-align-justify elementor-widget elementor-widget-button\" data-id=\"66462dd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/guillaume-guerard.com\/en\/\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Welcome<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<div class=\"elementor-column elementor-col-50 elementor-top-column elementor-element elementor-element-f579aa1\" data-id=\"f579aa1\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-98bab78 elementor-align-justify elementor-widget elementor-widget-button\" data-id=\"98bab78\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/complex-systems-ai.com\/\" target=\"_blank\" rel=\"noopener\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Data Science<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-7b200c2 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"7b200c2\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-9c029f8\" data-id=\"9c029f8\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-d16e1a0 elementor-widget elementor-widget-heading\" data-id=\"d16e1a0\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Page contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Contents\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/guillaume-guerard.com\/en\/cours-de-methodologie\/recherche-correlationnelle\/#Plan_scientifique_la_recherche_correlationnelle\" >Scientific plan: correlational research<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/guillaume-guerard.com\/en\/cours-de-methodologie\/recherche-correlationnelle\/#Methodes_et_methodologies\" >Methods and methodologies<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/guillaume-guerard.com\/en\/cours-de-methodologie\/recherche-correlationnelle\/#Bonnes_pratiques\" >Good practices<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/guillaume-guerard.com\/en\/cours-de-methodologie\/recherche-correlationnelle\/#Ce_quil_faut_eviter\" >What to avoid<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/guillaume-guerard.com\/en\/cours-de-methodologie\/recherche-correlationnelle\/#Conclusion\" >Conclusion<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Plan_scientifique_la_recherche_correlationnelle\"><\/span>Scientific plan: correlational research<span class=\"ez-toc-section-end\"><\/span><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-80f8b20 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"80f8b20\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-86ed04a\" data-id=\"86ed04a\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-5d7969e elementor-widget elementor-widget-text-editor\" data-id=\"5d7969e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Correlational research design focuses on examining relationships between variables without manipulation. Its goal is to determine whether and to what extent there is a relationship between two or more variables, thereby providing insight into patterns and trends. This type of research can identify associations, such as establishing a correlation between increased physical activity and decreased stress levels, without establishing a cause-and-effect relationship.<\/p><p><img decoding=\"async\" class=\"alignnone wp-image-49 size-full\" src=\"http:\/\/guillaume-guerard.com\/wp-content\/uploads\/2023\/07\/logo_sc.png\" alt=\"recherche corr\u00e9lationnelle\" width=\"238\" height=\"203\" \/><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-72efe70 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"72efe70\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-d5ccba1\" data-id=\"d5ccba1\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-f6346d4 elementor-widget elementor-widget-heading\" data-id=\"f6346d4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Methodes_et_methodologies\"><\/span>Methods and methodologies<span class=\"ez-toc-section-end\"><\/span><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3fe5b1c elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3fe5b1c\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-2cdeb47\" data-id=\"2cdeb47\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-dbe8de6 elementor-widget elementor-widget-text-editor\" data-id=\"dbe8de6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><strong>Statistical analysis<\/strong> \u2013 Statistical analyses are an integral part of correlational research because they quantify the strength and direction of relationships between variables. Methods used include Pearson correlation coefficient, Spearman rank correlation, and regression analysis. For example, a study might explore the relationship between income levels and education level using these tools.<\/p><p><strong><a href=\"https:\/\/guillaume-guerard.com\/en\/cours-de-methodologie\/\">Methodology<\/a> :<\/strong><\/p><p>Quantitative data are collected from reliable sources such as surveys, public datasets, or controlled observations. Researchers calculate correlation coefficients to assess the strength (e.g., strong, weak) and direction (e.g., positive, negative) of relationships. Tools such as SPSS, R, or Python facilitate data analysis. Data visualization, including scatter plots and heat maps, complements these analyses to illustrate relationships between variables.<\/p><p><strong>Correlation coefficients\u00a0<\/strong>\u2013 Correlation coefficients quantify the degree of relationship between variables. Commonly used types include:<br \/>Pearson correlation coefficient (r): measures linear relationships between two continuous variables, such as study hours and <a href=\"https:\/\/guillaume-guerard.com\/en\/cours-de-methodologie\/parfaire-la-section-resultats\/\">results<\/a> to the tests.<br \/>Spearman&#039;s rank correlation (\u03c1): Suitable for ordinal data or non-linear relationships, such as customer satisfaction and service quality ratings.<\/p><p><strong>Methodology:<\/strong><\/p><p>Researchers collect paired data points for variables of interest. Using statistical software, they calculate correlation coefficients, which range from -1 (perfect negative correlation) to +1 (perfect positive correlation), with 0 indicating no linear relationship. Visualization tools, such as scatter plots, are used to depict these relationships and identify outliers or potential patterns.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-d7aa689 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"d7aa689\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-78b3c1c\" data-id=\"78b3c1c\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-dcb234d elementor-widget elementor-widget-heading\" data-id=\"dcb234d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Bonnes_pratiques\"><\/span>Good practices<span class=\"ez-toc-section-end\"><\/span><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-de70f1e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"de70f1e\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-8164820\" data-id=\"8164820\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-1176b86 elementor-widget elementor-widget-text-editor\" data-id=\"1176b86\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><strong>Ensure valid and reliable data<\/strong>\u00a0:<br \/>Use well-designed tools to collect accurate, consistent, and unbiased data points for each variable.<\/p><p><strong>Testing the hypotheses<\/strong> :<br \/>Check that the data meets the assumptions of the <a href=\"https:\/\/guillaume-guerard.com\/en\/cours-de-methodologie\/parfaire-la-methodologie\/\">method<\/a> of chosen correlation, such as linearity and homoscedasticity for Pearson correlation.<\/p><p><strong>Consider the sample size<\/strong> :<br \/>Use a sufficiently large and representative sample to improve the reliability and generalizability of the results.<\/p><p><strong>Apply multiple tests<\/strong> :<br \/>Where appropriate, combine measures such as Pearson and Spearman correlations to confirm results, especially for ordinal or nonlinear data.<\/p><p><strong>Visualize the relationships<\/strong> :<br \/>Use scatter plots, heat maps, or other visual tools to illustrate relationships and identify trends or anomalies in the data.<\/p><p><strong>Control of confounding variables<\/strong> :<br \/>Use statistical controls or include additional variables in regression models to account for external factors that might influence the relationships.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ed98b8b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ed98b8b\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-7162f67\" data-id=\"7162f67\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-39c505e elementor-widget elementor-widget-heading\" data-id=\"39c505e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Ce_quil_faut_eviter\"><\/span>What to avoid<span class=\"ez-toc-section-end\"><\/span><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-1694229 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"1694229\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-a71ec90\" data-id=\"a71ec90\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-ccb2e6d elementor-widget elementor-widget-text-editor\" data-id=\"ccb2e6d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><strong>Assume causality<\/strong>\u00a0:<br \/>Correlation does not imply causation. For example, a correlation between ice cream sales and drowning rates does not mean that one causes the other.<\/p><p><strong>Ignore non-linear relationships<\/strong> :<br \/>Using linear methods only when variables have nonlinear relationships can lead to misleading conclusions.<\/p><p><strong>Neglecting confounding variables<\/strong> :<br \/>Failing to account for external variables that may influence the relationship can produce biased results.<\/p><p><strong>Bias in data collection<\/strong> :<br \/>Avoid sampling only specific subgroups or using faulty instruments that could skew the data.<\/p><p><strong>Overinterpretation of weak correlations<\/strong> :<br \/>A weak correlation coefficient, even if statistically significant, may not be meaningful in practice.<\/p><p><strong>Neglecting Outliers<\/strong> :<br \/>Failure to account for outliers can distort correlation estimates and lead to inaccurate interpretations.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-c511c7e elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"c511c7e\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-4209fc5\" data-id=\"4209fc5\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-da8c176 elementor-widget elementor-widget-heading\" data-id=\"da8c176\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span>Conclusion<span class=\"ez-toc-section-end\"><\/span><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-3976601 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"3976601\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-ac75734\" data-id=\"ac75734\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-31e67ef elementor-widget elementor-widget-text-editor\" data-id=\"31e67ef\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p>Correlational research design is a powerful method for identifying and quantifying relationships between variables. By adhering to best practices, such as ensuring data reliability, visualizing relationships, and controlling for confounding, researchers can produce accurate and actionable information. While correlation cannot establish causation, it provides valuable associations that can guide further experimental or exploratory studies. This design is essential in fields ranging from social sciences to healthcare, where understanding relationships is crucial for informed decision-making and hypothesis generation.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>Home Data Science Scientific Plan: Correlational Research Correlational research design focuses on examining the \u2026 <\/p>","protected":false},"author":1,"featured_media":0,"parent":47,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"footnotes":""},"class_list":["post-1979","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/guillaume-guerard.com\/en\/wp-json\/wp\/v2\/pages\/1979","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/guillaume-guerard.com\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/guillaume-guerard.com\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/guillaume-guerard.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/guillaume-guerard.com\/en\/wp-json\/wp\/v2\/comments?post=1979"}],"version-history":[{"count":7,"href":"https:\/\/guillaume-guerard.com\/en\/wp-json\/wp\/v2\/pages\/1979\/revisions"}],"predecessor-version":[{"id":1987,"href":"https:\/\/guillaume-guerard.com\/en\/wp-json\/wp\/v2\/pages\/1979\/revisions\/1987"}],"up":[{"embeddable":true,"href":"https:\/\/guillaume-guerard.com\/en\/wp-json\/wp\/v2\/pages\/47"}],"wp:attachment":[{"href":"https:\/\/guillaume-guerard.com\/en\/wp-json\/wp\/v2\/media?parent=1979"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}