{"id":1336,"date":"2023-07-26T19:53:42","date_gmt":"2023-07-26T19:53:42","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%b4-%e1%84%8c%e1%85%a1%e1%86%ab%e1%84%8e%e1%85%a1-%e1%84%8c%e1%85%a6%e1%84%80%e1%85%a9%e1%86%b8%e1%84%92%e1%85%a1%e1%86%b8\/"},"modified":"2023-07-26T19:53:42","modified_gmt":"2023-07-26T19:53:42","slug":"%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%b4-%e1%84%8c%e1%85%a1%e1%86%ab%e1%84%8e%e1%85%a1-%e1%84%8c%e1%85%a6%e1%84%80%e1%85%a9%e1%86%b8%e1%84%92%e1%85%a1%e1%86%b8","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%b4-%e1%84%8c%e1%85%a1%e1%86%ab%e1%84%8e%e1%85%a1-%e1%84%8c%e1%85%a6%e1%84%80%e1%85%a9%e1%86%b8%e1%84%92%e1%85%a1%e1%86%b8\/","title":{"rendered":"Python\uc5d0\uc11c \uc794\ucc28 \uc81c\uacf1\ud569\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ko\/\u110c\u1161\u11ab\u110b\u1167\u1106\u116e\u11af\/\" target=\"_blank\" rel=\"noopener\">\uc794\ucc28\ub294<\/a> \ud68c\uadc0 \ubaa8\ub378\uc5d0\uc11c \uad00\uce21\ub41c \uac12\uacfc \uc608\uce21\ub41c \uac12 \uac04\uc758 \ucc28\uc774\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uacfc \uac19\uc774 \uacc4\uc0b0\ub429\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc794\ucc28 = \uad00\uce21\uac12 \u2013 \uc608\uce21\uac12<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ud68c\uadc0 \ubaa8\ub378\uc774 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \uc5bc\ub9c8\ub098 \uc798 \ub9de\ub294\uc9c0 \uc774\ud574\ud558\ub294 \ud55c \uac00\uc9c0 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc774 \uacc4\uc0b0\ub418\ub294 <strong>\uc794\ucc28 \uc81c\uacf1\ud569\uc744<\/strong> \uacc4\uc0b0\ud558\ub294 \uac83\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc794\ucc28 \uc81c\uacf1\ud569 = \u03a3(e <sub>i<\/sub> ) <sup>2<\/sup><\/span><\/p>\n<p> <span style=\"color: #000000;\">\uae08:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>\u03a3<\/strong> : &#8220;\ud569\uacc4&#8221;\ub97c \uc758\ubbf8\ud558\ub294 \uadf8\ub9ac\uc2a4 \uae30\ud638<\/span><\/li>\n<li> <span style=\"color: #000000;\"><strong>e <sub>i<\/sub><\/strong> : i <sup>\ubc88\uc9f8<\/sup> \uc794\uae30<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\uac12\uc774 \ub0ae\uc744\uc218\ub85d \ubaa8\ub378\uc774 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub354 \uc798 \ub9de\ub294 \uac83\uc785\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 Python\uc5d0\uc11c \ud68c\uadc0 \ubaa8\ub378\uc758 \uc794\ucc28 \uc81c\uacf1\ud569\uc744 \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc5d0 \ub300\ud55c \ub2e8\uacc4\ubcc4 \uc608\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>1\ub2e8\uacc4: \ub370\uc774\ud130 \uc785\ub825<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\uc774 \uc608\uc5d0\uc11c\ub294 \uacf5\ubd80\ud55c \uc2dc\uac04, \ucd1d \uc900\ube44 \uc2dc\ud5d8 \ud69f\uc218, 14\uba85\uc758 \ud559\uc0dd\uc774 \uc5bb\uc740 \uc2dc\ud5d8 \uacb0\uacfc\uc640 \uad00\ub828\ub41c \ub370\uc774\ud130\ub97c \uc785\ub825\ud569\ub2c8\ub2e4.<\/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;\">#createDataFrame<\/span>\ndf = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #008000;\">hours<\/span> ': [1, 2, 2, 4, 2, 1, 5, 4, 2, 4, 4, 3, 6, 5],\n                   ' <span style=\"color: #008000;\">exams<\/span> ': [1, 3, 3, 5, 2, 2, 1, 1, 0, 3, 4, 3, 2, 4],\n                   ' <span style=\"color: #008000;\">score<\/span> ': [76, 78, 85, 88, 72, 69, 94, 94, 88, 92, 90, 75, 96, 90]})\n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>2\ub2e8\uacc4: \ud68c\uadc0 \ubaa8\ub378 \uc801\ud569<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c\uc73c\ub85c, statsmodels \ub77c\uc774\ube0c\ub7ec\ub9ac\uc758<\/span> <a href=\"https:\/\/www.statsmodels.org\/devel\/generated\/statsmodels.regression.linear_model.OLS.html\" target=\"_blank\" rel=\"noopener noreferrer\">OLS() \ud568\uc218\ub97c<\/a> <span style=\"color: #000000;\">\uc0ac\uc6a9\ud558\uc5ec<\/span> &#8220;\uc2dc\uac04&#8221;\uacfc &#8220;\uc2dc\ud5d8&#8221;\uc744 \uc608\uce21 \ubcc0\uc218\ub85c, &#8220;\uc810\uc218&#8221;\ub97c \uc751\ub2f5 \ubcc0\uc218\ub85c \uc0ac\uc6a9\ud558\uc5ec \uc77c\ubc18 \ucd5c\uc18c \uc81c\uacf1 \ud68c\uadc0\ub97c \uc218\ud589\ud569\ub2c8\ub2e4.<\/p>\n<pre style=\"background-color: #ececec; 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 response variable\n<\/span>y = df[' <span style=\"color: #008000;\">score<\/span> ']\n\n<span style=\"color: #008080;\">#define predictor variables\n<\/span>x = df[[' <span style=\"color: #008000;\">hours<\/span> ', ' <span style=\"color: #008000;\">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: #993300;\">print<\/span> ( <span style=\"color: #3366ff;\">model.summary<\/span> ())\n\n                            OLS Regression Results                            \n==================================================== ============================\nDept. Variable: R-squared score: 0.722\nModel: OLS Adj. R-squared: 0.671\nMethod: Least Squares F-statistic: 14.27\nDate: Sat, 02 Jan 2021 Prob (F-statistic): 0.000878\nTime: 15:58:35 Log-Likelihood: -41.159\nNo. Comments: 14 AIC: 88.32\nDf Residuals: 11 BIC: 90.24\nModel: 2                                         \nCovariance Type: non-robust                                         \n==================================================== ============================\n                 coef std err t P&gt;|t| [0.025 0.975]\n-------------------------------------------------- ----------------------------\nconst 71.8144 3.680 19.517 0.000 63.716 79.913\nhours 5.0318 0.942 5.339 0.000 2.958 7.106\nexams -1.3186 1.063 -1.240 0.241 -3.658 1.021\n==================================================== ============================\nOmnibus: 0.976 Durbin-Watson: 1.270\nProb(Omnibus): 0.614 Jarque-Bera (JB): 0.757\nSkew: -0.245 Prob(JB): 0.685\nKurtosis: 1.971 Cond. No. 12.1\n==================================================== ============================\n<\/strong><\/span><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>3\ub2e8\uacc4: \uc794\ucc28 \uc81c\uacf1\ud569 \uacc4\uc0b0<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub97c \uc0ac\uc6a9\ud558\uc5ec \ubaa8\ub378\uc758 \uc794\ucc28 \uc81c\uacf1\ud569\uc744 \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #993300;\">print<\/span> ( <span style=\"color: #3366ff;\">model.ssr<\/span> )\n\n293.25612951525414\n<\/strong><\/span><\/pre>\n<p> <span style=\"color: #000000;\">\uc794\ucc28 \uc81c\uacf1\ud569\uc740 <strong>293,256<\/strong> \uc785\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n<p> <a href=\"https:\/\/statorials.org\/ko\/\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\u110b\u1174-\u1100\u1161\u11ab\u1103\u1161\u11ab\u1112\u1161\u11ab-\u1109\u1165\u11ab\u1112\u1167\u11bc-\u1112\u116c\u1100\u1171\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c \ub2e8\uc21c \uc120\ud615 \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><br \/> <a href=\"https:\/\/statorials.org\/ko\/\u1109\u1165\u11ab\u1112\u1167\u11bc-\u1112\u116c\u1100\u1171-\u1111\u1161\u110b\u1175\u110a\u1165\u11ab\/\" target=\"_blank\" rel=\"noopener\">Python\uc5d0\uc11c \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><br \/> \uc794\ucc28 \uc81c\uacf1\ud569 \uacc4\uc0b0\uae30<\/p>\n","protected":false},"excerpt":{"rendered":"<p>\uc794\ucc28\ub294 \ud68c\uadc0 \ubaa8\ub378\uc5d0\uc11c \uad00\uce21\ub41c \uac12\uacfc \uc608\uce21\ub41c \uac12 \uac04\uc758 \ucc28\uc774\uc785\ub2c8\ub2e4. \ub2e4\uc74c\uacfc \uac19\uc774 \uacc4\uc0b0\ub429\ub2c8\ub2e4. \uc794\ucc28 = \uad00\uce21\uac12 \u2013 \uc608\uce21\uac12 \ud68c\uadc0 \ubaa8\ub378\uc774 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \uc5bc\ub9c8\ub098 \uc798 \ub9de\ub294\uc9c0 \uc774\ud574\ud558\ub294 \ud55c \uac00\uc9c0 \ubc29\ubc95\uc740 \ub2e4\uc74c\uacfc \uac19\uc774 \uacc4\uc0b0\ub418\ub294 \uc794\ucc28 \uc81c\uacf1\ud569\uc744 \uacc4\uc0b0\ud558\ub294 \uac83\uc785\ub2c8\ub2e4. \uc794\ucc28 \uc81c\uacf1\ud569 = \u03a3(e i ) 2 \uae08: \u03a3 : &#8220;\ud569\uacc4&#8221;\ub97c \uc758\ubbf8\ud558\ub294 \uadf8\ub9ac\uc2a4 \uae30\ud638 e i : i \ubc88\uc9f8 \uc794\uae30 [&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-1336","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - 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