{"id":661,"date":"2020-09-22T02:30:40","date_gmt":"2020-09-22T02:30:40","guid":{"rendered":"https:\/\/support.divominer.com\/en\/index.php\/docs\/divominer-user-manual-2\/statistical-analysis\/granger-causality-analysis\/"},"modified":"2025-12-19T09:45:05","modified_gmt":"2025-12-19T09:45:05","slug":"granger-causality","status":"publish","type":"docs","link":"https:\/\/support.divominer.com\/en\/docs\/divominer-user-manual\/statistical-analysis\/granger-causality\/","title":{"rendered":"Granger causality"},"content":{"rendered":"\n<p><span lang=\"EN-US\">Granger causality is a statistical method to investigate causality between two variables in a time series, like whether a set of time series X is the cause of another set of time series Y. It is based on an autoregressive model in regression analysis. Regression analysis usually only yields the contemporaneous correlation between different variables; the autoregressive model can only obtain the correlation between the previous and the second variables; but the Nobel Prize winner in economics, Clive Granger found that it is feasible to reveal the time-difference correlation between different variables through a series of tests in the autoregressive model.<\/span><\/p>\n\n\n\n<p><span lang=\"EN-US\">The conclusion of the Granger causality test is statistical causality, not necessarily causality in the true sense of the word. But because the causal relationship in the statistical sense is also meaningful, it has certain reference value.<\/span><\/p>\n\n\n\n<p><span lang=\"EN-US\">When the P-value is less than 0.05, the null hypothesis is rejected, and vice versa.<\/span><\/p>\n\n\n\n<p><span lang=\"EN-US\">Drag one variable in the \u201cDimension\u201d field, then two variables in the \u201cValue\u201d field, and click Granger causality in the Statistical module to calculate the causality between variables.<\/span><\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" width=\"1024\" height=\"520\" src=\"https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2021\/11\/45-1-1024x520.png\" alt=\"\" class=\"wp-image-8481\" srcset=\"https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2021\/11\/45-1-1024x520.png 1024w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2021\/11\/45-1-300x152.png 300w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2021\/11\/45-1-768x390.png 768w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2021\/11\/45-1-50x25.png 50w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2021\/11\/45-1-920x467.png 920w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2021\/11\/45-1-600x305.png 600w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2021\/11\/45-1-320x162.png 320w, https:\/\/support.divominer.com\/en\/wp-content\/uploads\/2021\/11\/45-1.png 1330w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/figure>\n","protected":false},"featured_media":0,"parent":573,"menu_order":9,"comment_status":"open","ping_status":"closed","template":"","doc_tag":[],"_links":{"self":[{"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/661"}],"collection":[{"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs"}],"about":[{"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/types\/docs"}],"replies":[{"embeddable":true,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/comments?post=661"}],"version-history":[{"count":14,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/661\/revisions"}],"predecessor-version":[{"id":9460,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/661\/revisions\/9460"}],"up":[{"embeddable":true,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/573"}],"next":[{"title":"Chart type","link":"https:\/\/support.divominer.com\/en\/docs\/divominer-user-manual\/statistical-analysis\/chart-type\/","href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/611"}],"prev":[{"title":"Unary regression analysis","link":"https:\/\/support.divominer.com\/en\/docs\/divominer-user-manual\/statistical-analysis\/regression-analysis\/","href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/docs\/663"}],"wp:attachment":[{"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/media?parent=661"}],"wp:term":[{"taxonomy":"doc_tag","embeddable":true,"href":"https:\/\/support.divominer.com\/en\/wp-json\/wp\/v2\/doc_tag?post=661"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}