{"id":1598,"date":"2023-07-25T17:12:43","date_gmt":"2023-07-25T17:12:43","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%a6%e1%84%89%e1%85%a5-%e1%84%8f%e1%85%a1%e1%84%8b%e1%85%b5-%e1%84%8c%e1%85%a6%e1%84%80%e1%85%a9%e1%86%b8-%e1%84%87\/"},"modified":"2023-07-25T17:12:43","modified_gmt":"2023-07-25T17:12:43","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%a6%e1%84%89%e1%85%a5-%e1%84%8f%e1%85%a1%e1%84%8b%e1%85%b5-%e1%84%8c%e1%85%a6%e1%84%80%e1%85%a9%e1%86%b8-%e1%84%87","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%a6%e1%84%89%e1%85%a5-%e1%84%8f%e1%85%a1%e1%84%8b%e1%85%b5-%e1%84%8c%e1%85%a6%e1%84%80%e1%85%a9%e1%86%b8-%e1%84%87\/","title":{"rendered":"Python\uc5d0\uc11c \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec\ub97c \uadf8\ub9ac\ub294 \ubc29\ubc95"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">Python\uc5d0\uc11c \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec\ub97c \uadf8\ub9ac\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#x-axis ranges from 0 to 20 with .001 steps\n<\/span>x = np. <span style=\"color: #3366ff;\">arange<\/span> (0, 20, 0.001)\n\n<span style=\"color: #008080;\">#plot Chi-square distribution with 4 degrees of freedom\n<\/span>plt. <span style=\"color: #3366ff;\">plot<\/span> (x, chi2. <span style=\"color: #3366ff;\">pdf<\/span> (x, df= <span style=\"color: #008000;\">4<\/span> ))\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>x<\/strong> \ubc30\uc5f4\uc740 x\ucd95\uc758 \ubc94\uc704\ub97c \uc815\uc758\ud558\uace0 <strong>plt.plot()\uc740<\/strong> \uc9c0\uc815\ub41c \uc790\uc720\ub3c4\ub97c \uc0ac\uc6a9\ud558\uc5ec \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec\uc758 \ud50c\ub86f\uc744 \uc0dd\uc131\ud569\ub2c8\ub2e4.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \uc608\uc5d0\uc11c\ub294 \uc774\ub7ec\ud55c \uae30\ub2a5\uc744 \uc2e4\uc81c\ub85c \uc0ac\uc6a9\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 1: \ub2e8\uc77c \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec \uadf8\ub9ac\uae30<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \uc790\uc720\ub3c4\uac00 4\uc778 \ub2e8\uc77c \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec \uace1\uc120\uc744 \uadf8\ub9ac\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n<span style=\"color: #008000;\">from<\/span> scipy. <span style=\"color: #3366ff;\">stats<\/span> <span style=\"color: #008000;\">import<\/span> chi2\n\n<span style=\"color: #008080;\">#x-axis ranges from 0 to 20 with .001 steps\n<\/span>x = np. <span style=\"color: #3366ff;\">arange<\/span> (0, 20, 0.001)\n\n<span style=\"color: #008080;\">#plot Chi-square distribution with 4 degrees of freedom\n<\/span>plt. <span style=\"color: #3366ff;\">plot<\/span> (x, chi2. <span style=\"color: #3366ff;\">pdf<\/span> (x, df= <span style=\"color: #008000;\">4<\/span> ))<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-15903\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/chicarrepython1.png\" alt=\"Python\uc5d0\uc11c \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec \uadf8\ub9ac\uae30\" width=\"381\" height=\"243\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">\ucc28\ud2b8\uc5d0\uc11c \uc120\uc758 \uc0c9\uc0c1\uacfc \ub108\ube44\ub97c \ubcc0\uacbd\ud560 \uc218\ub3c4 \uc788\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>plt. <span style=\"color: #3366ff;\">plot<\/span> (x, chi2. <span style=\"color: #3366ff;\">pdf<\/span> (x, df= <span style=\"color: #008000;\">4<\/span> ), color=' <span style=\"color: #ff0000;\">red<\/span> ', linewidth= <span style=\"color: #008000;\">3<\/span> )<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-15901 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/chicarrepython2.png\" alt=\"\" width=\"394\" height=\"252\" srcset=\"\" sizes=\"auto, \"><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\uc608 2: \uc5ec\ub7ec \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec \ub3c4\ud45c\ud654<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\ub2e4\uc74c \ucf54\ub4dc\ub294 \ub2e4\uc591\ud55c \uc790\uc720\ub3c4\ub85c \uc5ec\ub7ec \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec \uace1\uc120\uc744 \uadf8\ub9ac\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n<span style=\"color: #008000;\">from<\/span> scipy. <span style=\"color: #3366ff;\">stats<\/span> <span style=\"color: #008000;\">import<\/span> chi2\n\n<span style=\"color: #008080;\">#x-axis ranges from 0 to 20 with .001 steps\n<\/span>x = np. <span style=\"color: #3366ff;\">arange<\/span> (0, 20, 0.001)\n\n<span style=\"color: #008080;\">#define multiple Chi-square distributions\n<\/span>plt. <span style=\"color: #3366ff;\">plot<\/span> (x, chi2. <span style=\"color: #3366ff;\">pdf<\/span> (x, df= <span style=\"color: #008000;\">4<\/span> ), label=' <span style=\"color: #ff0000;\">df: 4<\/span> ')\nplt. <span style=\"color: #3366ff;\">plot<\/span> (x, chi2. <span style=\"color: #3366ff;\">pdf<\/span> (x, df= <span style=\"color: #008000;\">8<\/span> ), label=' <span style=\"color: #ff0000;\">df: 8<\/span> ') \nplt. <span style=\"color: #3366ff;\">plot<\/span> (x, chi2. <span style=\"color: #3366ff;\">pdf<\/span> (x, df= <span style=\"color: #008000;\">12<\/span> ), label=' <span style=\"color: #ff0000;\">df: 12<\/span> ') \n\n<span style=\"color: #008080;\">#add legend to plot\n<\/span>plt. <span style=\"color: #3366ff;\">legend<\/span> ()<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\" wp-image-15904 aligncenter\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/chicarrepython3.png\" alt=\"\" width=\"398\" height=\"263\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\">\uc790\uc720\ub86d\uac8c \uc120 \uc0c9\uc0c1\uc744 \ubcc0\uacbd\ud558\uace0 \uc81c\ubaa9\uacfc \ucd95 \ub808\uc774\ube14\uc744 \ucd94\uac00\ud558\uc5ec \ucc28\ud2b8\ub97c \uc644\uc131\ud558\uc138\uc694.<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> numpy <span style=\"color: #008000;\">as<\/span> np\n<span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n<span style=\"color: #008000;\">from<\/span> scipy. <span style=\"color: #3366ff;\">stats<\/span> <span style=\"color: #008000;\">import<\/span> chi2\n\n<span style=\"color: #008080;\">#x-axis ranges from 0 to 20 with .001 steps\n<\/span>x = np. <span style=\"color: #3366ff;\">arange<\/span> (0, 20, 0.001)\n\n<span style=\"color: #008080;\">#define multiple Chi-square distributions\n<\/span>plt. <span style=\"color: #3366ff;\">plot<\/span> (x, chi2. <span style=\"color: #3366ff;\">pdf<\/span> (x, df= <span style=\"color: #008000;\">4<\/span> ), label=' <span style=\"color: #ff0000;\">df: 4<\/span> ', color=' <span style=\"color: #ff0000;\">gold<\/span> ')\nplt. <span style=\"color: #3366ff;\">plot<\/span> (x, chi2. <span style=\"color: #3366ff;\">pdf<\/span> (x, df= <span style=\"color: #008000;\">8<\/span> ), label=' <span style=\"color: #ff0000;\">df: 8<\/span> ', color=' <span style=\"color: #ff0000;\">red<\/span> ')\nplt. <span style=\"color: #3366ff;\">plot<\/span> (x, chi2. <span style=\"color: #3366ff;\">pdf<\/span> (x, df= <span style=\"color: #008000;\">12<\/span> ), label=' <span style=\"color: #ff0000;\">df: 12<\/span> ', color=' <span style=\"color: #ff0000;\">pink<\/span> ') \n\n<span style=\"color: #008080;\">#add legend to plot\n<\/span>plt. <span style=\"color: #3366ff;\">legend<\/span> (title=' <span style=\"color: #ff0000;\">Parameters<\/span> ')\n\n<span style=\"color: #008080;\">#add axes labels and a title\n<\/span>plt. <span style=\"color: #3366ff;\">ylabel<\/span> (' <span style=\"color: #ff0000;\">Density<\/span> ')\nplt. <span style=\"color: #3366ff;\">xlabel<\/span> (' <span style=\"color: #ff0000;\">x<\/span> ')\nplt. <span style=\"color: #3366ff;\">title<\/span> (' <span style=\"color: #ff0000;\">Chi-Square Distributions<\/span> ', fontsize= <span style=\"color: #008000;\">14<\/span> )<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-15905\" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/chicarrepython4-2.png\" alt=\"Python\uc5d0\uc11c \uc5ec\ub7ec \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec \uadf8\ub9ac\uae30\" width=\"435\" height=\"298\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p> <span style=\"color: #000000;\"><strong>plt.plot()<\/strong> \ud568\uc218\uc5d0 \ub300\ud55c \uc790\uc138\ud55c \uc124\uba85\uc740 <a href=\"https:\/\/matplotlib.org\/stable\/api\/_as_gen\/matplotlib.pyplot.plot.html\" target=\"_blank\" rel=\"noopener\">matplotlib \uc124\uba85\uc11c\ub97c<\/a> \ucc38\uc870\ud558\uc138\uc694.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Python\uc5d0\uc11c \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec\ub97c \uadf8\ub9ac\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. #x-axis ranges from 0 to 20 with .001 steps x = np. arange (0, 20, 0.001) #plot Chi-square distribution with 4 degrees of freedom plt. plot (x, chi2. pdf (x, df= 4 )) x \ubc30\uc5f4\uc740 x\ucd95\uc758 \ubc94\uc704\ub97c \uc815\uc758\ud558\uace0 plt.plot()\uc740 \uc9c0\uc815\ub41c \uc790\uc720\ub3c4\ub97c \uc0ac\uc6a9\ud558\uc5ec \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec\uc758 \ud50c\ub86f\uc744 \uc0dd\uc131\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-1598","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 \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec\ub97c \uadf8\ub9ac\ub294 \ubc29\ubc95<\/title>\n<meta name=\"description\" content=\"\uc774 \ud29c\ud1a0\ub9ac\uc5bc\uc5d0\uc11c\ub294 \uba87 \uac00\uc9c0 \uc608\ub97c \ud1b5\ud574 Python\uc5d0\uc11c \uce74\uc774\uc81c\uacf1 \ubd84\ud3ec\ub97c \uadf8\ub9ac\ub294 \ubc29\ubc95\uc744 \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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