{"width":"100%","published":"2020-07-30 00:50:59","title":"t\u5206\u5e03\u3078\u306e\u9053 (7)","image_url":null,"blog_url":"https://randommemory.hatenablog.com/","author_url":"https://blog.hatena.ne.jp/derwind/","blog_title":"\u3089\u3093\u3060\u3080\u306a\u8a18\u61b6","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Frandommemory.hatenablog.com%2Fentry%2F2020%2F07%2F30%2F005059\" title=\"t\u5206\u5e03\u3078\u306e\u9053 (7) - \u3089\u3093\u3060\u3080\u306a\u8a18\u61b6\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","height":"190","url":"https://randommemory.hatenablog.com/entry/2020/07/30/005059","author_name":"derwind","description":"$X_1, \\cdots, X_n \\sim N(\\mu,\\sigma^2)$ i.i.d. \u3068\u3059\u308b\u3002\u3053\u306e\u6642 $Y = \\frac{(n-1)s^2}{\\sigma^2}$ \u304c $Y \\sim \\chi_{n-1}^2$ \u3067\u3042\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3059\u308b\u3053\u3068\u304c\u6700\u5f8c\u306e\u8ab2\u984c\u3067\u3042\u3063\u305f\u3002\u3068\u3053\u308d\u3067\u3001 $Y$ \u306f \\begin{align} Y = \\sum_{k=1}^n \\frac{(X_k - \\bar{X})^2}{\\sigma^2} = \\sum_{k=1}^n \\left( \\frac{X_k - \\bar{X}}{\\sigma} \\right)^2 \\end{align}\u3068\u306a\u308b\u3002\u3068\u3053\u308d\u3067\u3001$\\frac{\u2026","provider_url":"https://hatena.blog","version":"1.0","provider_name":"Hatena Blog","categories":["statistics","math-probability"],"type":"rich"}