{"description":"Mean (\u5e73\u5747) x_mean = ( \\sigma_{1}^{n} ( x_i ) ) / n y_mean = ( \\sigma_{1}^{n} ( y_i ) ) / n Variance (\u5206\u6563) s_x^2 = ( \\sigma_{1}^{n} ( x_i - x_mean )^2 ) / n s_y^2 = ( \\sigma_{1}^{n} ( y_i - y_mean )^2 ) / n Root-mean-square deviation (\u6a19\u6e96\u504f\u5dee) s_x = sqrt( s_x^2 ) s_y = sqrt( s_y^2 ) This operation is done\u2026","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Fhanecci.hatenadiary.org%2Fentry%2F20130102%2Fp1\" title=\" Basic terms for multivariate analysis technique ( \u591a\u5909\u91cf\u89e3\u6790\u306e\u305f\u3081\u306e\u57fa\u672c\u7528\u8a9e ) - OLD hanecci\u2019s blog : \u65e7 \u306f\u306d\u3063\u3061\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>","author_name":"hanecci","provider_url":"https://hatena.blog","title":" Basic terms for multivariate analysis technique ( \u591a\u5909\u91cf\u89e3\u6790\u306e\u305f\u3081\u306e\u57fa\u672c\u7528\u8a9e )","author_url":"https://blog.hatena.ne.jp/hanecci/","published":"2013-01-02 00:00:01","image_url":null,"version":"1.0","url":"https://hanecci.hatenadiary.org/entry/20130102/p1","height":"190","provider_name":"Hatena Blog","type":"rich","width":"100%","blog_title":"OLD hanecci\u2019s blog : \u65e7 \u306f\u306d\u3063\u3061\u30d6\u30ed\u30b0","categories":[],"blog_url":"https://hanecci.hatenadiary.org/"}