{"id":3811,"date":"2023-07-15T09:50:14","date_gmt":"2023-07-15T09:50:14","guid":{"rendered":"https:\/\/statorials.org\/ko\/python%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%90%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3%e1%84%92%e1%85%a1%e1%86%af-%e1%84%84%e1%85%a2-goldfeld\/"},"modified":"2023-07-15T09:50:14","modified_gmt":"2023-07-15T09:50:14","slug":"python%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%90%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3%e1%84%92%e1%85%a1%e1%86%af-%e1%84%84%e1%85%a2-goldfeld","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/python%e1%84%8b%e1%85%b3%e1%86%af-%e1%84%90%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3%e1%84%92%e1%85%a1%e1%86%af-%e1%84%84%e1%85%a2-goldfeld\/","title":{"rendered":"Python\uc5d0\uc11c goldfeld-quandt \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>Goldfeld-Quandt \ud14c\uc2a4\ud2b8\ub294<\/strong> \ud68c\uadc0 \ubaa8\ub378\uc5d0 <a href=\"https:\/\/statorials.org\/ko\/\u110b\u1175\u1107\u116e\u11ab\u1109\u1161\u11ab\u1109\u1165\u11bc-\u1112\u116c\u1100\u1171\/\" target=\"_blank\" rel=\"noopener\">\uc774\ubd84\uc0b0\uc131\uc774<\/a> \uc874\uc7ac\ud558\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ubd84\uc0b0\uc131\uc740 \ud68c\uadc0 \ubaa8\ub378\uc5d0\uc11c <a href=\"https:\/\/statorials.org\/ko\/\u1107\u1167\u11ab\u1109\u116e-\u1109\u1165\u11af\u1106\u1167\u11bc-\u110b\u1173\u11bc\u1103\u1161\u11b8\/\" target=\"_blank\" rel=\"noopener\">\ubc18\uc751 \ubcc0\uc218<\/a> \uc758 \ub2e4\uc591\ud55c \uc218\uc900\uc5d0\uc11c <a href=\"https:\/\/statorials.org\/ko\/\u110c\u1161\u11ab\u110b\u1167\u1106\u116e\u11af\/\" target=\"_blank\" rel=\"noopener\">\uc794\ucc28\uac00<\/a> \ub3d9\uc77c\ud558\uc9c0 \uc54a\uac8c \ubd84\uc0b0\ub418\ub294 \uac83\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774\ubd84\uc0b0\uc131\uc774 \uc874\uc7ac\ud558\ub294 \uacbd\uc6b0 \uc774\ub294 \uc794\ucc28\uac00 \ubc18\uc751 \ubcc0\uc218\uc758 \uac01 \uc218\uc900\uc5d0 \ub3d9\uc77c\ud558\uac8c \ubd84\uc0b0\ub418\uc5b4 \uc788\ub2e4\ub294 <a href=\"https:\/\/statorials.org\/ko\/\u1109\u1165\u11ab\u1112\u1167\u11bc-\u1112\u116c\u1100\u1171-\u1100\u1161\u110c\u1165\u11bc\/\" target=\"_blank\" rel=\"noopener\">\uc120\ud615 \ud68c\uadc0 \ubd84\uc11d\uc758 \uc8fc\uc694 \uac00\uc815<\/a> \uc911 \ud558\ub098\ub97c \uc704\ubc18\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c Goldfeld-Quandt \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud55c \ub2e8\uacc4\ubcc4 \uc608\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h2> <strong>1\ub2e8\uacc4: \ub370\uc774\ud130\uc138\ud2b8 \ub9cc\ub4e4\uae30<\/strong><\/h2>\n<p> <span style=\"color: #000000;\">\uc774 \uc608\uc5d0\uc11c\ub294 \uc218\uc5c5 \uc2dc\uac04, \uc751\uc2dc\ud55c \uc900\ube44 \uc2dc\ud5d8, \uc218\uc5c5 \uc911 13\uba85\uc758 \ud559\uc0dd\uc774 \uc5bb\uc740 \ucd5c\uc885 \uc2dc\ud5d8 \uacb0\uacfc\uc5d0 \ub300\ud55c \uc815\ubcf4\uac00 \ud3ec\ud568\ub41c \ub2e4\uc74c pandas DataFrame\uc744 \ub9cc\ub4e4\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#createDataFrame\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #ff0000;\">hours<\/span> ': [1, 2, 2, 4, 2, 1, 5, 4, 2, 4, 4, 3, 6],\n                   ' <span style=\"color: #ff0000;\">exams<\/span> ': [1, 3, 3, 5, 2, 2, 1, 1, 0, 3, 4, 3, 2],\n                   ' <span style=\"color: #ff0000;\">score<\/span> ': [76, 78, 85, 88, 72, 69, 94, 94, 88, 92, 90, 75, 96]})\n\n<span style=\"color: #008080;\">#view DataFrame\n<\/span><span style=\"color: #008000;\">print<\/span> (df)\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<\/strong><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>2\ub2e8\uacc4: \uc120\ud615 \ud68c\uadc0 \ubaa8\ub378 \ud53c\ud305<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uc73c\ub85c <strong>\uc2dc\uac04<\/strong> \uacfc <strong>\uc2dc\ud5d8\uc744<\/strong> \uc608\uce21 \ubcc0\uc218\ub85c \uc0ac\uc6a9\ud558\uace0 <strong>\uc810\uc218\ub97c<\/strong> \uc751\ub2f5 \ubcc0\uc218\ub85c \uc0ac\uc6a9\ud558\uc5ec \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0 \ubaa8\ub378\uc744 \uc801\ud569\ud569\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008000;\">import<\/span> statsmodels. <span style=\"color: #3366ff;\">api<\/span> <span style=\"color: #008000;\">as<\/span> sm\n\n<span style=\"color: #008080;\">#define predictor and response variables\n<\/span>y = df[' <span style=\"color: #ff0000;\">score<\/span> ']\nx = df[[' <span style=\"color: #ff0000;\">hours<\/span> ', ' <span style=\"color: #ff0000;\">exams<\/span> ']]\n\n<span style=\"color: #008080;\">#add constant to predictor variables\n<\/span>x = sm. <span style=\"color: #3366ff;\">add_constant<\/span> (x)\n\n<span style=\"color: #008080;\">#fit linear regression model\n<\/span>model = sm. <span style=\"color: #3366ff;\">OLS<\/span> (y,x). <span style=\"color: #3366ff;\">fit<\/span> ()\n\n<span style=\"color: #008080;\">#view model summary\n<\/span><span style=\"color: #008000;\">print<\/span> ( <span style=\"color: #3366ff;\">model.summary<\/span> ())\n\n                            OLS Regression Results                            \n==================================================== ============================\nDept. Variable: R-squared score: 0.718\nModel: OLS Adj. R-squared: 0.661\nMethod: Least Squares F-statistic: 12.70\nDate: Mon, 31 Oct 2022 Prob (F-statistic): 0.00180\nTime: 09:22:56 Log-Likelihood: -38.618\nNo. Observations: 13 AIC: 83.24\nDf Residuals: 10 BIC: 84.93\nModel: 2                                         \nCovariance Type: non-robust                                         \n==================================================== ============================\n                 coef std err t P&gt;|t| [0.025 0.975]\n-------------------------------------------------- ----------------------------\nconst 71.4048 4.001 17.847 0.000 62.490 80.319\nhours 5.1275 1.018 5.038 0.001 2.860 7.395\nexams -1.2121 1.147 -1.057 0.315 -3.768 1.344\n==================================================== ============================\nOmnibus: 1,103 Durbin-Watson: 1,248\nProb(Omnibus): 0.576 Jarque-Bera (JB): 0.803\nSkew: -0.289 Prob(JB): 0.669\nKurtosis: 1.928 Cond. No. 11.7\n==================================================== ============================\n<\/strong><\/span><\/pre>\n<h2> <span style=\"color: #000000;\"><strong>3\ub2e8\uacc4: Goldfeld-Quandt \ud14c\uc2a4\ud2b8 \uc218\ud589<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uc73c\ub85c <strong>statsmodels<\/strong> <strong>het_goldfeldquandt()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Goldfeld-Quandt \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>\ucc38\uace0<\/strong> : Goldfeld-Quandt \ud14c\uc2a4\ud2b8\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uc758 \uc911\uc559\uc5d0 \uc788\ub294 \uc5ec\ub7ec \uad00\uce21\uce58\ub97c \uc81c\uac70\ud55c \ub2e4\uc74c \uc794\ucc28 \ubd84\ud3ec\uac00 \uc911\uc559 \uad00\uce21\uce58\uc758 \uc591\ucabd\uc5d0 \ubc14\uc778\ub529\ub41c \ub450 \uacb0\uacfc \ub370\uc774\ud130 \uc138\ud2b8\uc640 \ub2e4\ub978\uc9c0 \ud14c\uc2a4\ud2b8\ud558\ub294 \ubc29\uc2dd\uc73c\ub85c \uc791\ub3d9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc77c\ubc18\uc801\uc73c\ub85c \uc804\uccb4 \uad00\uce21\uce58\uc758 \uc57d 20%\ub97c \uc81c\uac70\ud558\ub3c4\ub85d \uc120\ud0dd\ud569\ub2c8\ub2e4. \uc774 \uacbd\uc6b0 <strong>drop<\/strong> \uc778\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uad00\uce21\uac12\uc758 20%\ub97c \uc81c\uac70\ud558\ub3c4\ub85d \uc9c0\uc815\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#perform Goldfeld-Quandt test\n<\/span>sm. <span style=\"color: #3366ff;\">stats<\/span> . <span style=\"color: #3366ff;\">diagnosis<\/span> . <span style=\"color: #3366ff;\">het_goldfeldquandt<\/span> (y, x, drop= <span style=\"color: #008000;\">0.2<\/span> )\n\n(1.7574505407790355, 0.38270288684680076, 'increasing')<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\uacb0\uacfc\ub97c \ud574\uc11d\ud558\ub294 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">\uac80\uc815 \ud1b5\uacc4\ub7c9\uc740 <b>1.757<\/b> \uc785\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\">\ud574\ub2f9 p-\uac12\uc740 <strong>0.383<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">Goldfeld-Quandt \uac80\uc815\uc740 \ub2e4\uc74c\uacfc \uac19\uc740 \uadc0\ubb34 \uac00\uc124\uacfc \ub300\ub9bd \uac00\uc124\uc744 \uc0ac\uc6a9\ud569\ub2c8\ub2e4.<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>Null (H <sub>0<\/sub> )<\/strong> : \ub3d9\ubd84\uc0b0\uc131\uc774 \uc874\uc7ac\ud569\ub2c8\ub2e4.<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>\ub300\uc548( <sub>HA<\/sub> ):<\/strong> \uc774\ubd84\uc0b0\uc131\uc774 \uc874\uc7ac\ud569\ub2c8\ub2e4.<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">p-\uac12\uc774 0.05 \uc774\uc0c1\uc774\ubbc0\ub85c \uadc0\ubb34\uac00\uc124\uc744 \uae30\uac01\ud560 \uc218 \uc5c6\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ud68c\uadc0 \ubaa8\ub378\uc5d0\uc11c \uc774\ubd84\uc0b0\uc131\uc774 \ubb38\uc81c\ub77c\uace0 \uc8fc\uc7a5\ud560 \ucda9\ubd84\ud55c \uc99d\uac70\uac00 \uc5c6\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h2> <strong>\ub2e4\uc74c\uc5d0 \ubb34\uc5c7\uc744\ud560\uc9c0<\/strong><\/h2>\n<p> <span style=\"color: #000000;\">Goldfeld-Quandt \uac80\uc815\uc758 \uadc0\ubb34 \uac00\uc124\uc744 \uae30\uac01\ud558\uc9c0 \ubabb\ud558\uba74 \uc774\ubd84\uc0b0\uc131\uc774 \uc874\uc7ac\ud558\uc9c0 \uc54a\uc73c\uba70 \uacc4\uc18d\ud574\uc11c \uc6d0\ub798 \ud68c\uadc0 \uacb0\uacfc\ub97c \ud574\uc11d\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uadf8\ub7ec\ub098 \uadc0\ubb34 \uac00\uc124\uc744 \uae30\uac01\ud558\uba74 \ub370\uc774\ud130\uc5d0 \uc774\ubd84\uc0b0\uc131\uc774 \uc874\uc7ac\ud55c\ub2e4\ub294 \uc758\ubbf8\uc785\ub2c8\ub2e4. \uc774 \uacbd\uc6b0 \ud68c\uadc0 \ucd9c\ub825 \ud14c\uc774\ube14\uc5d0 \ud45c\uc2dc\ub418\ub294 \ud45c\uc900 \uc624\ub958\ub294 \uc2e0\ub8b0\ud560 \uc218 \uc5c6\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ubb38\uc81c\ub97c \ud574\uacb0\ud558\ub294 \uba87 \uac00\uc9c0 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1. \ubc18\uc751 \ubcc0\uc218\ub97c \ubcc0\ud658\ud569\ub2c8\ub2e4.<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc608\ub97c \ub4e4\uc5b4 \uc751\ub2f5 \ubcc0\uc218\uc758 <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\u110b\u1173\u1105\u1169-\u1103\u1166\u110b\u1175\u1110\u1165-\u1107\u1167\u11ab\u1112\u116a\u11ab\/\" target=\"_blank\" rel=\"noopener\">\ub85c\uadf8, \uc81c\uacf1\uadfc \ub610\ub294 \uc138\uc81c\uacf1\uadfc\uc744<\/a> \ucde8\ud558\ub294 \ub4f1 \uc751\ub2f5 \ubcc0\uc218\uc5d0 \ub300\ud55c \ubcc0\ud658\uc744 \uc218\ud589\ud574 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c \uc774\ub85c \uc778\ud574 \uc774\ubd84\uc0b0\uc131\uc774 \uc0ac\ub77c\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2. \uac00\uc911 \ud68c\uadc0\ub97c \uc0ac\uc6a9\ud558\uc2ed\uc2dc\uc624.<\/strong><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uac00\uc911 \ud68c\uadc0\ub294 \uc801\ud569\uce58\uc758 \ubd84\uc0b0\uc744 \uae30\ubc18\uc73c\ub85c \uac01 \ub370\uc774\ud130 \ud3ec\uc778\ud2b8\uc5d0 \uac00\uc911\uce58\ub97c \ud560\ub2f9\ud569\ub2c8\ub2e4. \ubcf8\uc9c8\uc801\uc73c\ub85c \uc774\ub294 \ubd84\uc0b0\uc774 \ub354 \ub192\uc740 \ub370\uc774\ud130 \ud3ec\uc778\ud2b8\uc5d0 \ub0ae\uc740 \uac00\uc911\uce58\ub97c \ubd80\uc5ec\ud558\uc5ec \uc794\ucc28 \uc81c\uacf1\uc744 \uc904\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc801\uc808\ud55c \uac00\uc911\uce58\ub97c \uc0ac\uc6a9\ud558\uba74 \uac00\uc911 \ud68c\uadc0\ub97c \ud1b5\ud574 \uc774\ubd84\uc0b0\uc131 \ubb38\uc81c\ub97c \ud574\uacb0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<h2> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h2>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ub2e4\ub978 \uc77c\ubc18\uc801\uc778 \uc791\uc5c5\uc744 \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc124\uba85\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/ko\/ols-\u1112\u116c\u1100\u1171-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c OLS \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1161\u110b\u1175\u110a\u1165\u11ab-\u110c\u1161\u11ab\u110e\u1161-\u1100\u1173\u1105\u1162\u1111\u1173\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c \uc794\ucc28 \ud50c\ub86f\uc744 \ub9cc\ub4dc\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/python\u110b\u1174-\u1112\u1174\u11ab\u1109\u1162\u11a8-\u1110\u1166\u1109\u1173\u1110\u1173\/\">Python\uc5d0\uc11c White\uc758 \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/breusch-\u110b\u1175\u1100\u116d\u1103\u1169-\u1110\u1166\u1109\u1173\u1110\u1173-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c Breusch-Pagan \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Goldfeld-Quandt \ud14c\uc2a4\ud2b8\ub294 \ud68c\uadc0 \ubaa8\ub378\uc5d0 \uc774\ubd84\uc0b0\uc131\uc774 \uc874\uc7ac\ud558\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4. \uc774\ubd84\uc0b0\uc131\uc740 \ud68c\uadc0 \ubaa8\ub378\uc5d0\uc11c \ubc18\uc751 \ubcc0\uc218 \uc758 \ub2e4\uc591\ud55c \uc218\uc900\uc5d0\uc11c \uc794\ucc28\uac00 \ub3d9\uc77c\ud558\uc9c0 \uc54a\uac8c \ubd84\uc0b0\ub418\ub294 \uac83\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4. \uc774\ubd84\uc0b0\uc131\uc774 \uc874\uc7ac\ud558\ub294 \uacbd\uc6b0 \uc774\ub294 \uc794\ucc28\uac00 \ubc18\uc751 \ubcc0\uc218\uc758 \uac01 \uc218\uc900\uc5d0 \ub3d9\uc77c\ud558\uac8c \ubd84\uc0b0\ub418\uc5b4 \uc788\ub2e4\ub294 \uc120\ud615 \ud68c\uadc0 \ubd84\uc11d\uc758 \uc8fc\uc694 \uac00\uc815 \uc911 \ud558\ub098\ub97c \uc704\ubc18\ud569\ub2c8\ub2e4. \uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c Goldfeld-Quandt \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud55c \ub2e8\uacc4\ubcc4 \uc608\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-3811","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Python\uc5d0\uc11c Goldfeld-Quandt \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95 \u2013 Statorials<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c Goldfeld-Quandt \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \uc608\uc81c\uc640 \ud568\uaed8 \uc124\uba85\ud569\ub2c8\ub2e4.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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