{"html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fwww.crosshyou.info%2Fentry%2F2021%2F06%2F13%2F090727\" title=\"OECD Doctors&#39; consultations data analysis 6 - using lm() function for linear regression - R\u3067\u4f55\u304b\u3092\u3057\u305f\u308a\u3001\u8aad\u66f8\u3092\u3059\u308b\u30d6\u30ed\u30b0\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","url":"https://www.crosshyou.info/entry/2021/06/13/090727","provider_name":"Hatena Blog","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/c/cross_hyou/20210613/20210613083954.jpg","type":"rich","provider_url":"https://hatena.blog","version":"1.0","height":"190","title":"OECD Doctors' consultations data analysis 6 - using lm() function for linear regression","categories":["Data_Analysis"],"width":"100%","author_url":"https://blog.hatena.ne.jp/cross_hyou/","description":"Photo by DAVID TANG on Unsplash www.crosshyou.info This post is following of above post. In this blog, I will do regression anaysis using lm() function in R. Let's go ahead. summary() function displays result. p-value is 0.4024, it is greater than 0.05, so this model is not valid model. Let's add 'r\u2026","blog_title":"R\u3067\u4f55\u304b\u3092\u3057\u305f\u308a\u3001\u8aad\u66f8\u3092\u3059\u308b\u30d6\u30ed\u30b0","blog_url":"https://www.crosshyou.info/","author_name":"cross_hyou","published":"2021-06-13 09:07:27"}