{"id":1310,"date":"2023-07-26T22:25:12","date_gmt":"2023-07-26T22:25:12","guid":{"rendered":"https:\/\/statorials.org\/id\/kalkulator-residu-yang-dinormalisasi\/"},"modified":"2023-07-26T22:25:12","modified_gmt":"2023-07-26T22:25:12","slug":"kalkulator-residu-yang-dinormalisasi","status":"publish","type":"post","link":"https:\/\/statorials.org\/id\/kalkulator-residu-yang-dinormalisasi\/","title":{"rendered":"Kalkulator residu standar"},"content":{"rendered":"<p><script src=\"https:\/\/cdnjs.cloudflare.com\/ajax\/libs\/mathjs\/5.1.1\/math.js\"><\/script><script src=\"https:\/\/cdn.jsdelivr.net\/npm\/jstat@latest\/dist\/jstat.min.js\"><\/script><\/p>\n<style>\n@import url('https:\/\/fonts.googleapis.com\/css?family=Droid+Serif|Raleway');<\/p>\n<p>h1 {\ntext-align: center;\nfont-size: 50px;\nmargin-bottom: 0px;\nfont-family: 'Raleway', serif;\n}<\/p>\n<p>p {\ncolor: black;\nmargin-bottom: 15px;\nmargin-top: 15px;\nfont-family: 'Raleway', sans-serif;\n}<\/p>\n<p>#words {\npadding-left: 30px;\ncolor: black;\nfont-family: Raleway;\nmax-width: 550px;\nmargin: 25px auto;\nline-height: 1.75;\n}<\/p>\n<p>#words_summary {\npadding-left: 70px;\ncolor: black;\nfont-family: Raleway;\nmax-width: 550px;\nmargin: 25px auto;\nline-height: 1.75;\n}<\/p>\n<p>#words_text {\ncolor: black;\nfont-family: Raleway;\nmax-width: 550px;\nmargin: 25px auto;\nline-height: 1.75;\n}<\/p>\n<p>#words_text_area {\ndisplay:inline-block;\ncolor: black;\nfont-family: Raleway;\nmax-width: 550px;\nmargin: 25px auto;\nline-height: 1.75;\npadding-left: 100px;\n}<\/p>\n<p>#calcTitle {\ntext-align: center;\nfont-size: 20px;\nmargin-bottom: 0px;\nfont-family: 'Raleway', serif;\n}<\/p>\n<p>#hr_top {\nwidth: 30%;\nmargin-bottom: 0px;\nborder: none;\nheight: 2px;\ncolor: black;\nbackground-color: black;\n}<\/p>\n<p>#hr_bottom {\nwidth: 30%;\nmargin-top: 15px;\nborder: none;\nheight: 2px;\ncolor: black;\nbackground-color: black;\n}<\/p>\n<p>#words_table label, #words_table input {\n    display: inline-block;\n    vertical-align: baseline;\n    width: 350px;\n}<\/p>\n<p>    #buttonCalc {\n      border: 1px solid;\n      border-radius: 10px;\n      margin-top: 20px;<\/p>\n<p>      cursor: pointer;\n      outline: none;\n      background-color: white;\n      color: black;\n      font-family: 'Work Sans', sans-serif;\n      border: 1px solid grey;\n      \/* Green *\/\n    }<\/p>\n<p>    #buttonCalc:hover {\n      background-color: #f6f6f6;\n      border: 1px solid black;\n    }<\/p>\n<p>\t#words_table {\ncolor: black;\nfont-family: Raleway;\nmax-width: 350px;\nmargin: 25px auto;\nline-height: 1.75;\n}<\/p>\n<p>#summary_table {\ncolor: black;\nfont-family: Raleway;\nmax-width: 550px;\nmargin: 25px auto;\nline-height: 1.75;\npadding-left: 20px;\n}<\/p>\n<p>\t.label_radio {\n\ttext-align: center;\n    }<\/p>\n<p>td, tr, th {\n    border: 1px solid black;\n}\ntable {\n    border-collapse: collapse;\n}\ntd, th {\n    min-width: 50px;\n    height: 21px;\n}\n    .label_radio {\n\ttext-align: center;\n}<\/p>\n<p>#text_area_input {\n\tpadding-left: 35%;\n\tfloat: left;\n}<\/p>\n<p>svg:not(:root) {\n  overflow: visible;\n}<\/p>\n<\/style>\n<div id=\"words\">\n<p style=\"text-align: left\"><b><a href=\"https:\/\/statorials.org\/id\/residu-terstandar\/\" target=\"_blank\" rel=\"noopener\">Residual terstandar<\/a><\/b> adalah residu dibagi deviasi standarnya. Ini dihitung sebagai berikut:<\/p>\n<p style=\"text-align: left\"> <strong>r <sub>i<\/sub> = e <sub>i<\/sub> \/ RSE\u221a <span style=\"border-top: 1px solid black;\">1-jam <sub>ii<\/sub><\/span><\/strong><\/p>\n<p style=\"text-align: left\"> Emas:<\/p>\n<ul>\n<li> e <sub>i<\/sub> : Residu <sup>ke<\/sup> -i<\/li>\n<li> RSE: kesalahan standar sisa model<\/li>\n<li> h <sub>ii<\/sub> : Meningkatnya observasi <sup>ke-i<\/sup><\/li>\n<\/ul>\n<p style=\"text-align: left\"> Kalkulator ini menemukan residu standar untuk setiap observasi dalam model regresi linier sederhana.<\/p>\n<p style=\"text-align: left\"> Cukup masukkan daftar nilai variabel prediktor dan variabel respon pada kotak di bawah, lalu klik tombol &#8220;Hitung&#8221;:<\/p>\n<\/div>\n<p style=\"text-align: center\"> <b>Nilai prediktif:<\/b><\/p>\n<div id=\"words_table\"><textarea id=\"x\" rows=\"5\" cols=\"40\"> 8, 12, 12, 13, 14, 16, 17, 22, 24, 26, 29, 30<\/textarea><\/div>\n<p style=\"text-align: center\"> <b>Nilai respons:<\/b><\/p>\n<div id=\"words_table\"><textarea id=\"y\" rows=\"5\" cols=\"40\"> 41, 42, 39, 37, 35, 39, 45, 46, 39, 49, 55, 57 <\/textarea><\/div>\n<div id=\"words_table\"><input type=\"button\" id=\"buttonCalc\" onclick=\"calc()\" value=\"Calculate\"><\/div>\n<div id=\"words_table\">\n<p> <b>Persamaan regresi linier:<\/b><\/p>\n<\/div>\n<div id=\"words_table\">\n<p> \u0177 = <span id=\"b\">29,6309<\/span> + ( <span id=\"a\">0,7553<\/span> )*x<\/p>\n<\/div>\n<div id=\"words_table\">\n<p> <b>Daftar residu standar:<\/b><\/p>\n<\/div>\n<div id=\"words_table\">\n<p style=\"text-align: left\"> <span id=\"resids_out\">-0,143<br \/> -3.104<br \/> 1.896<br \/> -0,064<br \/> 1.975<br \/> -0,906<br \/> 1.133<br \/> -0,787<\/span><\/p>\n<\/div>\n<div id=\"words_table\">\n<p style=\"text-align: center\"><span id=\"error_msg\"><\/span><\/p>\n<\/div>\n<p><script>\nfunction calc() {<\/p>\n<p>\/\/get input data\nvar x = document.getElementById('x').value.split(',').map(Number);\nvar y = document.getElementById('y').value.split(',').map(Number);<\/p>\n<p>\/\/check that both lists are equal length\nif (x.length - y.length == 0) {\ndocument.getElementById('error_msg').innerHTML = '';<\/p>\n<p>function linearRegression(y,x){\n        var lr = {};\n        var n = y.length;\n        var sum_x = 0;\n        var sum_y = 0;\n        var sum_xy = 0;\n        var sum_xx = 0;\n        var sum_yy = 0;<\/p>\n<p>        for (var i = 0; i < y.length; i++) {\n            sum_x += x[i];\n            sum_y += y[i];\n            sum_xy += (x[i]*y[i]);\n            sum_xx += (x[i]*x[i]);\n            sum_yy += (y[i]*y[i]);\n        } \n\n        lr['slope'] = (n * sum_xy - sum_x * sum_y) \/ (n*sum_xx - sum_x * sum_x);\n        lr['intercept'] = (sum_y - lr.slope * sum_x)\/n;\n        return lr;\n}\n\nvar lr = linearRegression(y, x);\nvar a = lr.slope;\nvar b = lr.intercept;\n\n\/\/calculate residuals\nresiduals = [];\n\nfor (var obs = 0; obs < y.length; obs++) {\nthis_resid = (y[obs] - (b - (-1*a*x[obs]))).toFixed(3);\nresiduals.push(this_resid);\n}\n\n\/\/calculate leverage\nlev_n = x.length;\nlev_mean = math.mean(x);\nlev_ss = 0;\n\n for (var i = 0; i < x.length; i++) {\n   lev_ss += (x[i]-lev_mean)*(x[i]-lev_mean);\n} \n\nleverages = [];\nfor (var j = 0; j < x.length; j++) {\nthis_leverage = 1\/lev_n-(-1*(Math.pow(x[j] -lev_mean, 2)))\/lev_ss;\nleverages.push(this_leverage);\n}\n\n\/\/calculate RSE\nvar xbar = math.mean(x);\nvar ybar = math.mean(y);\n\nlet xbar2_hold = 0\n\tfor (let i = 0; i < x.length; i++) {\n\t\txbar2_hold += Math.pow(x[i], 2);\n\t}\n\nvar xbar2 = xbar2_hold \/ x.length;\n\nlet sxx = 0\n\tfor (let i = 0; i < x.length; i++) {\n\t\tsxx += Math.pow(x[i] - xbar, 2);\n\t}\n\nlet syy = 0\n\tfor (let i = 0; i < y.length; i++) {\n\t\tsyy += Math.pow(y[i] - ybar, 2);\n\t}\n\nlet sxy = 0\n\tfor (let i = 0; i < x.length; i++) {\n\t\tsxy += (x[i] - xbar)*(y[i]-ybar);\n\t}\n\nlet sxx2 = 0\n\tfor (let i = 0; i < x.length; i++) {\n\t\tsxx2 += (x[i] - xbar)*(Math.pow(x[i], 2)-xbar2);\n\t}\n\nlet sx2x2 = 0\n\tfor (let i = 0; i < x.length; i++) {\n\t\tsx2x2 += Math.pow((Math.pow(x[i], 2)-xbar2), 2);\n\t}\n\nlet sx2y = 0\n\tfor (let i = 0; i < x.length; i++) {\n\t\tsx2y += (Math.pow(x[i], 2)-xbar2)*(y[i]-ybar);\n\t}\n\nvar sst = syy;\nvar ssr = (sxy\/sxx)*sxy;\nvar sse = sst-ssr;\n\nvar RSE = Math.sqrt(sse \/ (x.length - 2));\n\n\/\/calculate standardized residuals\nstand_resids = [];\nfor (var k = 0; k < x.length; k++) {\nthis_sr = (residuals[k]\/(RSE*Math.sqrt(1-leverages[k]))).toFixed(4);\nstand_resids.push(this_sr);\n}\n\n\/\/output results\ndocument.getElementById('a').innerHTML = a.toFixed(4);\ndocument.getElementById('b').innerHTML = b.toFixed(4);\ndocument.getElementById('resids_out').innerHTML = stand_resids.toString().split(',').join(\"<br \/>\");\n}<\/p>\n<p>\/\/output error message if both lists are not equal\nelse {\ndocument.getElementById('error_msg').innerHTML = 'The two lists must be of equal length.';\n}<\/p>\n<p>} \/\/end calc function\n<\/script><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Residual terstandar adalah residu dibagi deviasi standarnya. Ini dihitung sebagai berikut: r i = e i \/ RSE\u221a 1-jam ii Emas: e i : Residu ke -i RSE: kesalahan standar sisa model h ii : Meningkatnya observasi ke-i Kalkulator ini menemukan residu standar untuk setiap observasi dalam model regresi linier sederhana. Cukup masukkan daftar nilai [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Kalkulator Residual Standar - Statorial<\/title>\n<meta name=\"description\" content=\"Kalkulator ini menemukan residu standar untuk model regresi linier sederhana.\" \/>\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\/id\/kalkulator-residu-yang-dinormalisasi\/\" \/>\n<meta property=\"og:locale\" content=\"id_ID\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Kalkulator Residual Standar - Statorial\" \/>\n<meta property=\"og:description\" content=\"Kalkulator ini menemukan residu standar untuk model regresi linier sederhana.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/id\/kalkulator-residu-yang-dinormalisasi\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-26T22:25:12+00:00\" \/>\n<meta name=\"author\" content=\"Benjamin anderson\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Ditulis oleh\" \/>\n\t<meta name=\"twitter:data1\" content=\"Benjamin anderson\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/id\/kalkulator-residu-yang-dinormalisasi\/\",\"url\":\"https:\/\/statorials.org\/id\/kalkulator-residu-yang-dinormalisasi\/\",\"name\":\"Kalkulator Residual Standar - Statorial\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/id\/#website\"},\"datePublished\":\"2023-07-26T22:25:12+00:00\",\"dateModified\":\"2023-07-26T22:25:12+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\"},\"description\":\"Kalkulator ini menemukan residu standar untuk model regresi linier sederhana.\",\"breadcrumb\":{\"@id\":\"https:\/\/statorials.org\/id\/kalkulator-residu-yang-dinormalisasi\/#breadcrumb\"},\"inLanguage\":\"id\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/statorials.org\/id\/kalkulator-residu-yang-dinormalisasi\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/statorials.org\/id\/kalkulator-residu-yang-dinormalisasi\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/statorials.org\/id\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Kalkulator residu standar\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/id\/#website\",\"url\":\"https:\/\/statorials.org\/id\/\",\"name\":\"Statorials\",\"description\":\"Panduan anda untuk kompetensi statistik!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/id\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"id\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/3d17a1160dd2d052b7c78e502cb9ec81\",\"name\":\"Benjamin anderson\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"id\",\"@id\":\"https:\/\/statorials.org\/id\/#\/schema\/person\/image\/\",\"url\":\"http:\/\/statorials.org\/id\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"contentUrl\":\"http:\/\/statorials.org\/id\/wp-content\/uploads\/2023\/10\/Dr.-Benjamin-Anderson-96x96.jpg\",\"caption\":\"Benjamin anderson\"},\"description\":\"Halo, saya Benjamin, pensiunan profesor statistika yang menjadi guru Statorial yang berdedikasi. 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