{"id":880,"date":"2023-07-28T10:48:49","date_gmt":"2023-07-28T10:48:49","guid":{"rendered":"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/"},"modified":"2023-07-28T10:48:49","modified_gmt":"2023-07-28T10:48:49","slug":"%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/","title":{"rendered":"Python \u306e\u7dda\u5f62\u56de\u5e30\u306e\u5b8c\u5168\u30ac\u30a4\u30c9"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u7dda\u5f62\u56de\u5e30\u306f<\/strong>\u30011 \u3064\u4ee5\u4e0a\u306e\u4e88\u6e2c\u5909\u6570\u3068\u5fdc\u7b54\u5909\u6570\u306e\u9593\u306e\u95a2\u4fc2\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3067\u304d\u308b\u65b9\u6cd5\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u4f8b: Python \u3067\u306e\u7dda\u5f62\u56de\u5e30<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u52c9\u5f37\u306b\u8cbb\u3084\u3057\u305f\u6642\u9593\u6570\u3068\u53d7\u3051\u305f\u6a21\u64ec\u8a66\u9a13\u306e\u6570\u304c\u3001\u5b66\u751f\u304c\u7279\u5b9a\u306e\u8a66\u9a13\u3067\u53d7\u3051\u53d6\u308b\u6210\u7e3e\u306b\u5f71\u97ff\u3059\u308b\u304b\u3069\u3046\u304b\u3092\u77e5\u308a\u305f\u3044\u3068\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u4fc2\u3092\u8abf\u67fb\u3059\u308b\u306b\u306f\u3001Python \u3067\u6b21\u306e\u624b\u9806\u3092\u5b9f\u884c\u3057\u3066\u91cd\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 1: \u30c7\u30fc\u30bf\u3092\u5165\u529b\u3057\u307e\u3059\u3002<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u307e\u305a\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u4fdd\u6301\u3059\u308b\u30d1\u30f3\u30c0 DataFrame \u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create data<\/span>\ndf = pd.DataFrame({'hours': [1, 2, 2, 4, 2, 1, 5, 4, 2, 4, 4, 3, 6, 5, 3, 4, 6, 2, 1, 2],\n                   'exams': [1, 3, 3, 5, 2, 2, 1, 1, 0, 3, 4, 3, 2, 4, 4, 4, 5, 1, 0, 1],\n                   'score': [76, 78, 85, 88, 72, 69, 94, 94, 88, 92, 90, 75, 96, 90, 82, 85, 99, 83, 62, 76]})\n<span style=\"color: #008080;\">\n#view data<\/span> \ndf\n\n        hours exam score\n0 1 1 76\n1 2 3 78\n2 2 3 85\n3 4 5 88\n4 2 2 72\n5 1 2 69\n6 5 1 94\n7 4 1 94\n8 2 0 88\n9 4 3 92\n10 4 4 90\n11 3 3 75\n12 6 2 96\n13 5 4 90\n14 3 4 82\n15 4 4 85\n16 6 5 99\n17 2 1 83\n18 1 0 62\n19 2 1 76\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 2: \u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306b\u3001statsmodels \u30e9\u30a4\u30d6\u30e9\u30ea\u306e<a href=\"https:\/\/www.statsmodels.org\/devel\/generated\/statsmodels.regression.linear_model.OLS.html\" target=\"_blank\" rel=\"noopener noreferrer\">OLS() \u95a2\u6570<\/a>\u3092\u4f7f\u7528\u3057\u3066\u3001\u300c\u6642\u9593\u300d\u3068\u300c\u8a66\u9a13\u300d\u3092\u4e88\u6e2c\u5909\u6570\u3068\u3057\u3066\u3001\u300c\u30b9\u30b3\u30a2\u300d\u3092\u5fdc\u7b54\u5909\u6570\u3068\u3057\u3066\u4f7f\u7528\u3057\u3066\u3001\u901a\u5e38\u306e\u6700\u5c0f\u4e8c\u4e57\u56de\u5e30\u3092\u5b9f\u884c\u3057\u307e\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> statsmodels.api <span style=\"color: #107d3f;\">as<\/span> sm\n\n<span style=\"color: #008080;\">#define response variable\n<\/span>y = df['score']\n\n<span style=\"color: #008080;\">#define predictor variables\n<\/span>x = df[['hours', 'exams']]\n\n<span style=\"color: #008080;\">#add constant to predictor variables\n<\/span>x = sm.add_constant(x)\n\n<span style=\"color: #008080;\">#fit linear regression model\n<\/span>model = sm.OLS(y, x).fit()\n\n<span style=\"color: #008080;\">#view model summary\n<\/span>print(model.summary())\n\n                            OLS Regression Results                            \n==================================================== ============================\nDept. Variable: R-squared score: 0.734\nModel: OLS Adj. R-squared: 0.703\nMethod: Least Squares F-statistic: 23.46\nDate: Fri, 24 Jul 2020 Prob (F-statistic): 1.29e-05\nTime: 13:20:31 Log-Likelihood: -60.354\nNo. Observations: 20 AIC: 126.7\nDf Residuals: 17 BIC: 129.7\nDf Model: 2                                         \nCovariance Type: non-robust                                         \n==================================================== ============================\n                 coef std err t P&gt;|t| [0.025 0.975]\n-------------------------------------------------- ----------------------------\nconst 67.6735 2.816 24.033 0.000 61.733 73.614\nhours 5.5557 0.899 6.179 0.000 3.659 7.453\nexams -0.6017 0.914 -0.658 0.519 -2.531 1.327\n==================================================== ============================\nOmnibus: 0.341 Durbin-Watson: 1.506\nProb(Omnibus): 0.843 Jarque-Bera (JB): 0.196\nSkew: -0.216 Prob(JB): 0.907\nKurtosis: 2,782 Cond. No. 10.8\n==================================================== ============================\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 3: \u7d50\u679c\u3092\u89e3\u91c8\u3057\u307e\u3059\u3002<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u7d50\u679c\u5185\u306e\u6700\u3082\u95a2\u9023\u6027\u306e\u9ad8\u3044\u6570\u5024\u3092\u89e3\u91c8\u3059\u308b\u65b9\u6cd5\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>R \u306e 2 \u4e57:<\/strong> <strong>0.734<\/strong> \u3002\u3053\u308c\u3092\u6c7a\u5b9a\u4fc2\u6570\u3068\u3044\u3044\u307e\u3059\u3002\u3053\u308c\u306f\u3001\u4e88\u6e2c\u5909\u6570\u306b\u3088\u3063\u3066\u8aac\u660e\u3067\u304d\u308b\u5fdc\u7b54\u5909\u6570\u306e\u5206\u6563\u306e\u5272\u5408\u3067\u3059\u3002\u3053\u306e\u4f8b\u3067\u306f\u3001\u8a66\u9a13\u5f97\u70b9\u306e\u5909\u52d5\u306e 73.4% \u306f\u3001\u52c9\u5f37\u6642\u9593\u6570\u3068\u53d7\u9a13\u3057\u305f\u4e88\u5099\u8a66\u9a13\u306e\u6570\u306b\u3088\u3063\u3066\u8aac\u660e\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>F \u7d71\u8a08: 23.46<\/strong> \u3002\u3053\u308c\u306f\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u5168\u4f53\u7684\u306a F \u7d71\u8a08\u91cf\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u78ba\u7387 (F \u7d71\u8a08\u91cf): 1.29e-05\u3002<\/strong>\u3053\u308c\u306f\u3001\u5168\u4f53\u7684\u306a F \u7d71\u8a08\u91cf\u306b\u95a2\u9023\u4ed8\u3051\u3089\u308c\u305f p \u5024\u3067\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u56de\u5e30\u30e2\u30c7\u30eb\u5168\u4f53\u304c\u7d71\u8a08\u7684\u306b\u6709\u610f\u3067\u3042\u308b\u304b\u3069\u3046\u304b\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u8a00\u3044\u63db\u3048\u308c\u3070\u3001\u7d44\u307f\u5408\u308f\u305b\u305f 2 \u3064\u306e\u4e88\u6e2c\u5909\u6570\u304c\u5fdc\u7b54\u5909\u6570\u3068\u7d71\u8a08\u7684\u306b\u6709\u610f\u306a\u95a2\u9023\u6027\u3092\u6301\u3063\u3066\u3044\u308b\u304b\u3069\u3046\u304b\u304c\u308f\u304b\u308a\u307e\u3059\u3002\u3053\u306e\u5834\u5408\u3001p \u5024\u306f 0.05 \u672a\u6e80\u3067\u3042\u308a\u3001\u4e88\u6e2c\u5909\u6570\u300c\u5b66\u7fd2\u6642\u9593\u300d\u3068\u300c\u53d7\u9a13\u3057\u305f\u4e88\u5099\u8a66\u9a13\u300d\u306e\u7d44\u307f\u5408\u308f\u305b\u304c\u8a66\u9a13\u30b9\u30b3\u30a2\u3068\u7d71\u8a08\u7684\u306b\u6709\u610f\u306a\u95a2\u9023\u6027\u304c\u3042\u308b\u3053\u3068\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>coef:<\/strong>\u5404\u4e88\u6e2c\u5b50\u5909\u6570\u306e\u4fc2\u6570\u306f\u3001\u4ed6\u306e\u4e88\u6e2c\u5b50\u5909\u6570\u304c\u4e00\u5b9a\u306e\u307e\u307e\u3067\u3042\u308b\u3068\u4eee\u5b9a\u3057\u305f\u5834\u5408\u3001\u5fdc\u7b54\u5909\u6570\u306e\u4e88\u60f3\u3055\u308c\u308b\u5e73\u5747\u5909\u5316\u3092\u793a\u3057\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u3001\u53d7\u9a13\u3057\u305f\u6a21\u64ec\u8a66\u9a13\u304c\u4e00\u5b9a\u3067\u3042\u308b\u3068\u4eee\u5b9a\u3059\u308b\u3068\u3001\u52c9\u5f37\u306b\u8cbb\u3084\u3059\u6642\u9593\u304c\u3055\u3089\u306b 1 \u6642\u9593\u5897\u3048\u308b\u3054\u3068\u306b\u3001\u8a66\u9a13\u306e\u5e73\u5747\u5f97\u70b9\u306f<strong>5.56 \u70b9<\/strong>\u5897\u52a0\u3059\u308b\u3068\u4e88\u60f3\u3055\u308c\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5225\u306e\u898b\u65b9\u3092\u3059\u308b\u3068\u3001\u751f\u5f92 A \u3068\u751f\u5f92 B \u304c\u540c\u3058\u56de\u6570\u306e\u4e88\u5099\u8a66\u9a13\u3092\u53d7\u3051\u3001\u751f\u5f92 A \u304c 1 \u6642\u9593\u9577\u304f\u52c9\u5f37\u3057\u305f\u5834\u5408\u3001\u751f\u5f92 A \u306e\u5f97\u70b9\u306f\u751f\u5f92 B \u3088\u308a<strong>5.56<\/strong>\u70b9\u9ad8\u304f\u306a\u308b\u306f\u305a\u3067\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5207\u7247\u4fc2\u6570\u306f\u3001\u4f55\u6642\u9593\u3082\u52c9\u5f37\u305b\u305a\u3001\u4e88\u5099\u8a66\u9a13\u3082\u53d7\u3051\u306a\u304b\u3063\u305f\u751f\u5f92\u306e\u4e88\u60f3\u3055\u308c\u308b\u8a66\u9a13\u30b9\u30b3\u30a2\u304c<strong>67.67<\/strong>\u3067\u3042\u308b\u3053\u3068\u3092\u610f\u5473\u3059\u308b\u3068\u89e3\u91c8\u3057\u307e\u3059\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>P&gt;|t|\u3002<\/strong>\u500b\u3005\u306e p \u5024\u306f\u3001\u5404\u4e88\u6e2c\u5909\u6570\u304c\u7d71\u8a08\u7684\u306b\u6709\u610f\u3067\u3042\u308b\u304b\u3069\u3046\u304b\u3092\u793a\u3057\u307e\u3059\u3002 \u300c\u6642\u9593\u300d\u306f\u7d71\u8a08\u7684\u306b\u6709\u610f (p = 0.00) \u3067\u3042\u308b\u306e\u306b\u5bfe\u3057\u3001\u300c\u8a66\u9a13\u300d\u306f\u7d71\u8a08\u7684\u306b\u6709\u610f\u3067\u3042\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002 <strong>&nbsp;<\/strong> (p = 0.52) \u306f\u3001\u03b1 = 0.05 \u3067\u306f\u7d71\u8a08\u7684\u306b\u6709\u610f\u3067\u306f\u3042\u308a\u307e\u305b\u3093\u3002 \u300c\u8a66\u9a13\u300d\u3068\u3044\u3046\u7528\u8a9e\u306f\u7d71\u8a08\u7684\u306b\u6709\u610f\u3067\u306f\u306a\u3044\u305f\u3081\u3001\u6700\u7d42\u7684\u306b\u30e2\u30c7\u30eb\u304b\u3089\u524a\u9664\u3059\u308b\u3053\u3068\u3092\u6c7a\u5b9a\u3059\u308b\u53ef\u80fd\u6027\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u63a8\u5b9a\u56de\u5e30\u5f0f:<\/strong>\u30e2\u30c7\u30eb\u51fa\u529b\u306e\u4fc2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001\u6b21\u306e\u63a8\u5b9a\u56de\u5e30\u5f0f\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u8a66\u9a13\u30b9\u30b3\u30a2 = 67.67 + 5.56*(\u6642\u9593) \u2013 0.60*(\u6e96\u5099\u8a66\u9a13)<\/strong><\/span><\/p>\n<p data-slot-rendered-dynamic=\"true\"><span style=\"color: #000000;\">\u3053\u306e\u63a8\u5b9a\u56de\u5e30\u5f0f\u3092\u4f7f\u7528\u3057\u3066\u3001\u5b66\u7fd2\u6642\u9593\u6570\u3068\u53d7\u9a13\u3057\u305f\u6a21\u64ec\u8a66\u9a13\u306e\u6570\u306b\u57fa\u3065\u3044\u3066\u3001\u751f\u5f92\u306e\u4e88\u60f3\u3055\u308c\u308b\u8a66\u9a13\u30b9\u30b3\u30a2\u3092\u8a08\u7b97\u3067\u304d\u307e\u3059\u3002\u305f\u3068\u3048\u3070\u30013 \u6642\u9593\u52c9\u5f37\u3057\u3066\u4e88\u5099\u8a66\u9a13\u3092\u53d7\u3051\u308b\u5b66\u751f\u306f\u3001 <strong>83.75<\/strong>\u306e\u6210\u7e3e\u3092\u53d6\u5f97\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<p data-slot-rendered-dynamic=\"true\"><span style=\"color: #000000;\">\u904e\u53bb\u306e\u4e88\u5099\u8a66\u9a13\u306f\u7d71\u8a08\u7684\u306b\u6709\u610f\u3067\u306f\u306a\u304b\u3063\u305f\u306e\u3067 (p = 0.52)\u3001\u30e2\u30c7\u30eb\u5168\u4f53\u306b\u4f55\u306e\u6539\u5584\u3082\u3082\u305f\u3089\u3055\u306a\u3044\u305f\u3081\u3001\u8a66\u9a13\u3092\u524a\u9664\u3059\u308b\u3053\u3068\u3092\u6c7a\u5b9a\u3059\u308b\u5834\u5408\u304c\u3042\u308b\u3053\u3068\u306b\u7559\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u3053\u306e\u5834\u5408\u3001\u4e88\u6e2c\u5909\u6570\u3068\u3057\u3066\u8abf\u67fb\u3055\u308c\u305f\u6642\u9593\u306e\u307f\u3092\u4f7f\u7528\u3057\u3066\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p data-slot-rendered-dynamic=\"true\"><span style=\"color: #000000;\"><strong>\u30b9\u30c6\u30c3\u30d7 4: \u30e2\u30c7\u30eb\u306e\u4eee\u5b9a\u3092\u691c\u8a3c\u3057\u307e\u3059\u3002<\/strong><\/span><\/p>\n<p data-slot-rendered-dynamic=\"true\"><span style=\"color: #000000;\">\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3057\u305f\u3089\u3001\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u7d50\u679c\u304c\u4fe1\u983c\u3067\u304d\u308b\u3082\u306e\u3067\u3042\u308b\u3053\u3068\u3092\u78ba\u8a8d\u3059\u308b\u305f\u3081\u306b\u3001\u3044\u304f\u3064\u304b\u306e\u4eee\u5b9a\u3092\u30c1\u30a7\u30c3\u30af\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3053\u308c\u3089\u306e\u4eee\u5b9a\u306b\u306f\u6b21\u306e\u3082\u306e\u304c\u542b\u307e\u308c\u307e\u3059\u3002<\/span><\/p>\n<p data-slot-rendered-dynamic=\"true\"><span style=\"color: #000000;\"><strong>\u4eee\u5b9a #1:<\/strong>\u4e88\u6e2c\u5909\u6570\u3068\u5fdc\u7b54\u5909\u6570\u306e\u9593\u306b\u306f\u7dda\u5f62\u95a2\u4fc2\u304c\u3042\u308a\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li data-slot-rendered-dynamic=\"true\"><span style=\"color: #000000;\">\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u6b8b\u5dee\u306b\u5bfe\u3059\u308b\u8fd1\u4f3c\u5024\u3092\u8868\u793a\u3059\u308b<a href=\"https:\/\/statorials.org\/ja\/python\u6b8b\u5dee\u30af\u3099\u30e9\u30d5\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u6b8b\u5dee\u30d7\u30ed\u30c3\u30c8<\/a>\u3092\u751f\u6210\u3057\u3066\u3001\u3053\u306e\u4eee\u5b9a\u3092\u691c\u8a3c\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>\u4eee\u8aac #2:<\/strong>\u6b8b\u5dee\u306e\u72ec\u7acb\u6027\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/\u30bf\u3099\u30fc\u30d2\u3099\u30f3\u30fb\u30ef\u30c8\u30bd\u30f3\u30fb\u30c6\u30b9\u30c8python\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u30c0\u30fc\u30d3\u30f3-\u30ef\u30c8\u30bd\u30f3\u691c\u5b9a<\/a>\u3092\u5b9f\u884c\u3057\u3066\u3001\u3053\u306e\u4eee\u8aac\u3092\u691c\u8a3c\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>\u4eee\u8aac #3:<\/strong>\u6b8b\u5dee\u306e\u7b49\u5206\u6563\u6027\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/\u30d5\u3099\u30eb\u30fc\u30b7\u30e5\u7570\u6559\u306e\u30c6\u30b9\u30c8-python\/\" target=\"_blank\" rel=\"noopener noreferrer\">Breusch-Pagan \u691c\u5b9a<\/a>\u3092\u5b9f\u884c\u3057\u3066\u3001\u3053\u306e\u4eee\u8aac\u3092\u691c\u8a3c\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>\u4eee\u5b9a 4:<\/strong>\u6b8b\u5dee\u306e\u6b63\u898f\u6027\u3002<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/\u3044\u304f\u3064\u304b\u306epython\u30d5\u309a\u30ed\u30c3\u30c8\/\" target=\"_blank\" rel=\"noopener noreferrer\">QQ \u30d7\u30ed\u30c3\u30c8<\/a>\u3092\u4f7f\u7528\u3057\u3066\u3001\u3053\u306e\u4eee\u5b9a\u3092\u8996\u899a\u7684\u306b\u691c\u8a3c\u3057\u307e\u3059\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u3053\u306e\u4eee\u8aac\u3092\u3001 <a href=\"https:\/\/statorials.org\/ja\/jarque-\u306f\u30c6\u30b9\u30c8-python-\u306b\u306a\u308a\u307e\u3059\/\" target=\"_blank\" rel=\"noopener noreferrer\">Jarque-Bera \u30c6\u30b9\u30c8<\/a>\u3084<a href=\"https:\/\/statorials.org\/ja\/\u30a2\u30f3\u30bf\u3099\u30fc\u30bd\u30f3\u30fb\u30c1\u30a7\u30ea\u30fb\u30c6\u30b9\u30c8python\/\" target=\"_blank\" rel=\"noopener noreferrer\">Anderson-Darling \u30c6\u30b9\u30c8<\/a>\u306a\u3069\u306e\u6b63\u5f0f\u306a\u30c6\u30b9\u30c8\u3067\u691c\u8a3c\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\"><strong>\u4eee\u5b9a #5:<\/strong>\u4e88\u6e2c\u5909\u6570\u9593\u306b\u591a\u91cd\u5171\u7dda\u6027\u304c\u306a\u3044\u3053\u3068\u3092\u78ba\u8a8d\u3057\u307e\u3059\u3002<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u5404\u4e88\u6e2c\u5b50\u5909\u6570\u306e<a href=\"https:\/\/statorials.org\/ja\/python\u3066\u3099vive\u3092\u8a08\u7b97\u3059\u308b\u65b9\u6cd5\/\" target=\"_blank\" rel=\"noopener noreferrer\">VIF \u5024<\/a>\u3092\u8a08\u7b97\u3057\u3066\u3001\u3053\u306e\u4eee\u8aac\u3092\u691c\u8a3c\u3057\u307e\u3059\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u3053\u308c\u3089\u306e\u4eee\u5b9a\u304c\u6e80\u305f\u3055\u308c\u3066\u3044\u308c\u3070\u3001\u91cd\u7dda\u5f62\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u7d50\u679c\u304c\u4fe1\u983c\u3067\u304d\u308b\u3082\u306e\u3067\u3042\u308b\u3068\u78ba\u4fe1\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><em>\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u4f7f\u7528\u3055\u308c\u308b\u5b8c\u5168\u306a Python \u30b3\u30fc\u30c9\u306f\u3001 <a href=\"https:\/\/github.com\/Statorials\/Python-Guides\/blob\/main\/multiple_linear_regression.py\" target=\"_blank\" rel=\"noopener noreferrer\">\u3053\u3053\u3067<\/a>\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/em><\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u7dda\u5f62\u56de\u5e30\u306f\u30011 \u3064\u4ee5\u4e0a\u306e\u4e88\u6e2c\u5909\u6570\u3068\u5fdc\u7b54\u5909\u6570\u306e\u9593\u306e\u95a2\u4fc2\u3092\u7406\u89e3\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3067\u304d\u308b\u65b9\u6cd5\u3067\u3059\u3002 \u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001Python \u3067\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002 \u4f8b: Python \u3067\u306e\u7dda\u5f62\u56de\u5e30 \u52c9\u5f37\u306b\u8cbb\u3084\u3057 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-880","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python \u3067\u306e\u7dda\u5f62\u56de\u5e30\u306e\u5b8c\u5168\u30ac\u30a4\u30c9 - Statology<\/title>\n<meta name=\"description\" content=\"\u3053\u308c\u306f\u3001Python \u3067\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u5b8c\u5168\u306a\u30ac\u30a4\u30c9\u3067\u3059\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ja\/\u7dda\u5f62\u56de\u5e30python\/\" \/>\n<meta property=\"og:locale\" content=\"ja_JP\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python \u3067\u306e\u7dda\u5f62\u56de\u5e30\u306e\u5b8c\u5168\u30ac\u30a4\u30c9 - Statology\" \/>\n<meta property=\"og:description\" content=\"\u3053\u308c\u306f\u3001Python \u3067\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u5b8c\u5168\u306a\u30ac\u30a4\u30c9\u3067\u3059\u3002\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ja\/\u7dda\u5f62\u56de\u5e30python\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-28T10:48:49+00:00\" \/>\n<meta name=\"author\" content=\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u57f7\u7b46\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593\" \/>\n\t<meta name=\"twitter:data2\" content=\"1\u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/\",\"url\":\"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/\",\"name\":\"Python \u3067\u306e\u7dda\u5f62\u56de\u5e30\u306e\u5b8c\u5168\u30ac\u30a4\u30c9 - Statology\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/ja\/#website\"},\"datePublished\":\"2023-07-28T10:48:49+00:00\",\"dateModified\":\"2023-07-28T10:48:49+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83\"},\"description\":\"\u3053\u308c\u306f\u3001Python \u3067\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u5b8c\u5168\u306a\u30ac\u30a4\u30c9\u3067\u3059\u3002\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/#breadcrumb\"},\"inLanguage\":\"ja\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"\u5bb6\",\"item\":\"https:\/\/statorials.org\/ja\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Python \u306e\u7dda\u5f62\u56de\u5e30\u306e\u5b8c\u5168\u30ac\u30a4\u30c9\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/ja\/#website\",\"url\":\"https:\/\/statorials.org\/ja\/\",\"name\":\"Statorials\",\"description\":\"\u7d71\u8a08\u80fd\u529b\u3078\u306e\u30ac\u30a4\u30c9\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/ja\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"ja\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83\",\"name\":\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ja\",\"@id\":\"https:\/\/statorials.org\/ja\/#\/schema\/person\/image\/\",\"url\":\"http:\/\/statorials.org\/ja\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"http:\/\/statorials.org\/ja\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb\"},\"description\":\"\u79c1\u306f\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u3067\u3059\u3002\u9000\u8077\u3057\u305f\u7d71\u8a08\u6559\u6388\u304b\u3089\u3001\u5c02\u4efb\u306e Statorials \u6559\u80b2\u8005\u306b\u306a\u308a\u307e\u3057\u305f\u3002 \u7d71\u8a08\u5206\u91ce\u306b\u304a\u3051\u308b\u8c4a\u5bcc\u306a\u7d4c\u9a13\u3068\u5c02\u9580\u77e5\u8b58\u3092\u6d3b\u304b\u3057\u3066\u3001\u79c1\u306f Statorials \u3092\u901a\u3058\u3066\u5b66\u751f\u306b\u529b\u3092\u4e0e\u3048\u308b\u305f\u3081\u306b\u81ea\u5206\u306e\u77e5\u8b58\u3092\u5171\u6709\u3059\u308b\u3053\u3068\u306b\u5c3d\u529b\u3057\u3066\u3044\u307e\u3059\u3002\u3082\u3063\u3068\u77e5\u308b\",\"sameAs\":[\"http:\/\/statorials.org\/ja\"]}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Python \u3067\u306e\u7dda\u5f62\u56de\u5e30\u306e\u5b8c\u5168\u30ac\u30a4\u30c9 - Statology","description":"\u3053\u308c\u306f\u3001Python \u3067\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u5b8c\u5168\u306a\u30ac\u30a4\u30c9\u3067\u3059\u3002","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/statorials.org\/ja\/\u7dda\u5f62\u56de\u5e30python\/","og_locale":"ja_JP","og_type":"article","og_title":"Python \u3067\u306e\u7dda\u5f62\u56de\u5e30\u306e\u5b8c\u5168\u30ac\u30a4\u30c9 - Statology","og_description":"\u3053\u308c\u306f\u3001Python \u3067\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u5b8c\u5168\u306a\u30ac\u30a4\u30c9\u3067\u3059\u3002","og_url":"https:\/\/statorials.org\/ja\/\u7dda\u5f62\u56de\u5e30python\/","og_site_name":"Statorials","article_published_time":"2023-07-28T10:48:49+00:00","author":"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb","twitter_card":"summary_large_image","twitter_misc":{"\u57f7\u7b46\u8005":"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb","\u63a8\u5b9a\u8aad\u307f\u53d6\u308a\u6642\u9593":"1\u5206"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/","url":"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/","name":"Python \u3067\u306e\u7dda\u5f62\u56de\u5e30\u306e\u5b8c\u5168\u30ac\u30a4\u30c9 - Statology","isPartOf":{"@id":"https:\/\/statorials.org\/ja\/#website"},"datePublished":"2023-07-28T10:48:49+00:00","dateModified":"2023-07-28T10:48:49+00:00","author":{"@id":"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83"},"description":"\u3053\u308c\u306f\u3001Python \u3067\u7dda\u5f62\u56de\u5e30\u3092\u5b9f\u884c\u3059\u308b\u65b9\u6cd5\u306b\u95a2\u3059\u308b\u5b8c\u5168\u306a\u30ac\u30a4\u30c9\u3067\u3059\u3002","breadcrumb":{"@id":"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/#breadcrumb"},"inLanguage":"ja","potentialAction":[{"@type":"ReadAction","target":["https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/statorials.org\/ja\/%e7%b7%9a%e5%bd%a2%e5%9b%9e%e5%b8%b0python\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"\u5bb6","item":"https:\/\/statorials.org\/ja\/"},{"@type":"ListItem","position":2,"name":"Python \u306e\u7dda\u5f62\u56de\u5e30\u306e\u5b8c\u5168\u30ac\u30a4\u30c9"}]},{"@type":"WebSite","@id":"https:\/\/statorials.org\/ja\/#website","url":"https:\/\/statorials.org\/ja\/","name":"Statorials","description":"\u7d71\u8a08\u80fd\u529b\u3078\u306e\u30ac\u30a4\u30c9","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/statorials.org\/ja\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"ja"},{"@type":"Person","@id":"https:\/\/statorials.org\/ja\/#\/schema\/person\/86b92d2dd87368b26360d19d9c6a5d83","name":"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb","image":{"@type":"ImageObject","inLanguage":"ja","@id":"https:\/\/statorials.org\/ja\/#\/schema\/person\/image\/","url":"http:\/\/statorials.org\/ja\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg","contentUrl":"http:\/\/statorials.org\/ja\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg","caption":"\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u30fb\u30a2\u30f3\u30c0\u30fc\u30bd\u30f3\u535a\u58eb"},"description":"\u79c1\u306f\u30d9\u30f3\u30b8\u30e3\u30df\u30f3\u3067\u3059\u3002\u9000\u8077\u3057\u305f\u7d71\u8a08\u6559\u6388\u304b\u3089\u3001\u5c02\u4efb\u306e Statorials \u6559\u80b2\u8005\u306b\u306a\u308a\u307e\u3057\u305f\u3002 \u7d71\u8a08\u5206\u91ce\u306b\u304a\u3051\u308b\u8c4a\u5bcc\u306a\u7d4c\u9a13\u3068\u5c02\u9580\u77e5\u8b58\u3092\u6d3b\u304b\u3057\u3066\u3001\u79c1\u306f Statorials \u3092\u901a\u3058\u3066\u5b66\u751f\u306b\u529b\u3092\u4e0e\u3048\u308b\u305f\u3081\u306b\u81ea\u5206\u306e\u77e5\u8b58\u3092\u5171\u6709\u3059\u308b\u3053\u3068\u306b\u5c3d\u529b\u3057\u3066\u3044\u307e\u3059\u3002\u3082\u3063\u3068\u77e5\u308b","sameAs":["http:\/\/statorials.org\/ja"]}]}},"yoast_meta":{"yoast_wpseo_title":"","yoast_wpseo_metadesc":"","yoast_wpseo_canonical":""},"_links":{"self":[{"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/posts\/880","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/comments?post=880"}],"version-history":[{"count":0,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/posts\/880\/revisions"}],"wp:attachment":[{"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/media?parent=880"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/categories?post=880"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/statorials.org\/ja\/wp-json\/wp\/v2\/tags?post=880"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}