{"id":28434,"date":"2023-06-20T18:17:37","date_gmt":"2023-06-20T21:17:37","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/psychedelic-medicine-copy\/"},"modified":"2023-07-03T18:36:10","modified_gmt":"2023-07-03T21:36:10","slug":"regression-analysis","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/hu\/regresszio-elemzes\/","title":{"rendered":"A regresszi\u00f3elemz\u00e9s haszn\u00e1lata az \u00f6sszetett kapcsolatok meg\u00e9rt\u00e9s\u00e9hez"},"content":{"rendered":"<p>A regresszi\u00f3elemz\u00e9s egy vagy t\u00f6bb f\u00fcggetlen v\u00e1ltoz\u00f3 \u00e9s egy f\u00fcgg\u0151 v\u00e1ltoz\u00f3 k\u00f6z\u00f6tti kapcsolat azonos\u00edt\u00e1s\u00e1ra \u00e9s elemz\u00e9s\u00e9re szolg\u00e1l\u00f3 megk\u00f6zel\u00edt\u00e9s. Ezt a m\u00f3dszert sz\u00e9les k\u00f6rben alkalmazz\u00e1k sz\u00e1mos tudom\u00e1ny\u00e1gban, t\u00f6bbek k\u00f6z\u00f6tt az eg\u00e9szs\u00e9g\u00fcgyben, a t\u00e1rsadalomtudom\u00e1nyokban, a m\u00e9rn\u00f6ki tudom\u00e1nyokban, a k\u00f6zgazdas\u00e1gtanban \u00e9s az \u00fczleti \u00e9letben. A regresszi\u00f3elemz\u00e9s seg\u00edts\u00e9g\u00e9vel megvizsg\u00e1lhatja az adatokban l\u00e9v\u0151 alapvet\u0151 \u00f6sszef\u00fcgg\u00e9seket, \u00e9s olyan el\u0151rejelz\u0151 modelleket dolgozhat ki, amelyek seg\u00edtik a megalapozott d\u00f6nt\u00e9sek meghozatal\u00e1t.<\/p>\n\n\n\n<p>Ez a cikk \u00e1tfog\u00f3 \u00e1ttekint\u00e9st ny\u00fajt a regresszi\u00f3elemz\u00e9sr\u0151l, bele\u00e9rtve annak m\u0171k\u00f6d\u00e9s\u00e9t, egy k\u00f6nnyen \u00e9rthet\u0151 p\u00e9ld\u00e1t, \u00e9s elmagyar\u00e1zza, miben k\u00fcl\u00f6nb\u00f6zik a korrel\u00e1ci\u00f3elemz\u00e9st\u0151l.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-what-is-regression-analysis\">Mi az a regresszi\u00f3elemz\u00e9s?<\/h2>\n\n\n\n<p>A regresszi\u00f3elemz\u00e9s egy statisztikai m\u00f3dszer a f\u00fcgg\u0151 v\u00e1ltoz\u00f3 \u00e9s egy vagy t\u00f6bb f\u00fcggetlen v\u00e1ltoz\u00f3 k\u00f6z\u00f6tti kapcsolat azonos\u00edt\u00e1s\u00e1ra \u00e9s sz\u00e1mszer\u0171s\u00edt\u00e9s\u00e9re. Di\u00f3h\u00e9jban seg\u00edt meg\u00e9rteni, hogy az egy vagy t\u00f6bb f\u00fcggetlen v\u00e1ltoz\u00f3ban bek\u00f6vetkez\u0151 v\u00e1ltoz\u00e1sok hogyan f\u00fcggenek \u00f6ssze a f\u00fcgg\u0151 v\u00e1ltoz\u00f3ban bek\u00f6vetkez\u0151 v\u00e1ltoz\u00e1sokkal.<\/p>\n\n\n\n<p>A regresszi\u00f3elemz\u00e9s alapos meg\u00e9rt\u00e9s\u00e9hez el\u0151sz\u00f6r is meg kell \u00e9rtenie a k\u00f6vetkez\u0151 fogalmakat:<\/p>\n\n\n\n<ul>\n<li><strong>F\u00fcgg\u0151 v\u00e1ltoz\u00f3: <\/strong>Ez az a v\u00e1ltoz\u00f3, amelynek elemz\u00e9se vagy el\u0151rejelz\u00e9se \u00e9rdekli. Ez az a kimeneti v\u00e1ltoz\u00f3, amelyet megpr\u00f3b\u00e1l meg\u00e9rteni \u00e9s megmagyar\u00e1zni.<\/li>\n\n\n\n<li><strong>F\u00fcggetlen v\u00e1ltoz\u00f3k: <\/strong>Ezek azok a v\u00e1ltoz\u00f3k, amelyekr\u0151l \u00fagy gondolja, hogy hat\u00e1ssal vannak a f\u00fcgg\u0151 v\u00e1ltoz\u00f3ra. Gyakran nevezik \u0151ket prediktor v\u00e1ltoz\u00f3knak, mivel arra szolg\u00e1lnak, hogy megj\u00f3solj\u00e1k vagy megmagyar\u00e1zz\u00e1k a f\u00fcgg\u0151 v\u00e1ltoz\u00f3ban bek\u00f6vetkez\u0151 v\u00e1ltoz\u00e1sokat.<\/li>\n<\/ul>\n\n\n\n<p>A regresszi\u00f3elemz\u00e9s sz\u00e1mos esetben alkalmazhat\u00f3, t\u00f6bbek k\u00f6z\u00f6tt a f\u00fcgg\u0151 v\u00e1ltoz\u00f3 j\u00f6v\u0151beli \u00e9rt\u00e9keinek el\u0151rejelz\u00e9s\u00e9re, a f\u00fcggetlen v\u00e1ltoz\u00f3k f\u00fcgg\u0151 v\u00e1ltoz\u00f3ra gyakorolt hat\u00e1s\u00e1nak meg\u00e9rt\u00e9s\u00e9re, valamint az adatgy\u0171jt\u00e9s sor\u00e1n a kiugr\u00f3 \u00e9rt\u00e9kek vagy szokatlan esem\u00e9nyek megtal\u00e1l\u00e1s\u00e1ra.<\/p>\n\n\n\n<p>A regresszi\u00f3elemz\u00e9s t\u00f6bb t\u00edpusba sorolhat\u00f3, bele\u00e9rtve az egyszer\u0171 line\u00e1ris regresszi\u00f3t, a logisztikus regresszi\u00f3t, a polinomi\u00e1lis regresszi\u00f3t \u00e9s a t\u00f6bbsz\u00f6r\u00f6s regresszi\u00f3t. A megfelel\u0151 regresszi\u00f3s modellt az adatok jellege \u00e9s a vizsg\u00e1lat t\u00e1rgya hat\u00e1rozza meg.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-how-does-regression-analysis-work\">Hogyan m\u0171k\u00f6dik a regresszi\u00f3elemz\u00e9s?<\/h2>\n\n\n\n<p>A regresszi\u00f3elemz\u00e9s c\u00e9lja a f\u00fcggetlen v\u00e1ltoz\u00f3k \u00e9s a f\u00fcgg\u0151 v\u00e1ltoz\u00f3 k\u00f6z\u00f6tti kapcsolatot t\u00fckr\u00f6z\u0151 legjobban illeszked\u0151 egyenes vagy g\u00f6rbe meghat\u00e1roz\u00e1sa. Ezt a legjobban illeszked\u0151 egyenest vagy g\u00f6rb\u00e9t olyan statisztikai m\u00f3dszerek seg\u00edts\u00e9g\u00e9vel hozz\u00e1k l\u00e9tre, amelyek cs\u00f6kkentik az adatgy\u0171jt\u00e9s sor\u00e1n a v\u00e1rt \u00e9s a val\u00f3s \u00e9rt\u00e9kek k\u00f6z\u00f6tti elt\u00e9r\u00e9seket.<\/p>\n\n\n\n<p>Az al\u00e1bbiakban a regresszi\u00f3elemz\u00e9s k\u00e9t leggyakoribb t\u00edpus\u00e1nak k\u00e9pleteit ismertetj\u00fck:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-single-linear-regression\">Egyetlen line\u00e1ris regresszi\u00f3<\/h3>\n\n\n\n<p>Az egyszer\u0171 line\u00e1ris regresszi\u00f3ban a legjobban illeszked\u0151 egyenest haszn\u00e1lod a k\u00e9t v\u00e1ltoz\u00f3: a f\u00fcggetlen v\u00e1ltoz\u00f3 (x) \u00e9s a f\u00fcgg\u0151 v\u00e1ltoz\u00f3 (y) k\u00f6z\u00f6tti kapcsolat bemutat\u00e1s\u00e1ra.<\/p>\n\n\n\n<p>A legjobb illeszked\u00e9s egyenese a k\u00f6vetkez\u0151 egyenlet seg\u00edts\u00e9g\u00e9vel \u00e1br\u00e1zolhat\u00f3: y = a + bx.<\/p>\n\n\n\n<p>Itt a a metsz\u00e9spont, b az egyenes meredeks\u00e9ge. A meredeks\u00e9g kisz\u00e1m\u00edt\u00e1s\u00e1hoz a k\u00f6vetkez\u0151 k\u00e9pletet haszn\u00e1ljuk: b = (n\u03a3(xy) - \u03a3x\u03a3y) \/ (n\u03a3(x<sup>2<\/sup>) - (\u03a3x)<sup>2<\/sup>), ahol n a megfigyel\u00e9sek sz\u00e1ma, \u03a3xy az x \u00e9s y szorzat\u00e1nak \u00f6sszege, \u03a3x \u00e9s \u03a3y az x \u00e9s y \u00f6sszegei, \u00e9s \u03a3(x<sup>2<\/sup>) az x n\u00e9gyzeteinek \u00f6sszege.<\/p>\n\n\n\n<p>A metsz\u00e9spont kisz\u00e1m\u00edt\u00e1s\u00e1hoz a k\u00f6vetkez\u0151 k\u00e9pletet kell haszn\u00e1lni: a = (\u03a3y - b\u03a3x) \/ n.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-multiple-regression\">T\u00f6bbsz\u00f6r\u00f6s regresszi\u00f3&nbsp;<\/h3>\n\n\n\n<p>T\u00f6bbsz\u00f6r\u00f6s line\u00e1ris regresszi\u00f3:<\/p>\n\n\n\n<p>A t\u00f6bbsz\u00f6r\u00f6s line\u00e1ris regresszi\u00f3s modell egyenlet\u00e9nek k\u00e9plete a k\u00f6vetkez\u0151:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote\">\n<p><strong>y = b<sub>0<\/sub> + b<sub>1<\/sub>x<sub>1<\/sub> + b<sub>2<\/sub>x<sub>2<\/sub> + ... + b<sub>n<\/sub>x<sub>n<\/sub><\/strong><\/p>\n<\/blockquote>\n\n\n\n<p>ahol y a f\u00fcgg\u0151 v\u00e1ltoz\u00f3, x<sub>1<\/sub>, x<sub>2<\/sub>, ..., x<sub>n<\/sub> a f\u00fcggetlen v\u00e1ltoz\u00f3k, \u00e9s b<sub>0<\/sub>, b<sub>1<\/sub>, b<sub>2<\/sub>, ..., bn a f\u00fcggetlen v\u00e1ltoz\u00f3k egy\u00fctthat\u00f3i.<\/p>\n\n\n\n<p>Az egy\u00fctthat\u00f3k becsl\u00e9s\u00e9re szolg\u00e1l\u00f3 k\u00e9plet a k\u00f6vetkez\u0151:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote\">\n<p><strong>\u03b2 = (X'X)<sup>(-1)<\/sup>X'y<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p>ahol \u03b2 az egy\u00fctthat\u00f3k oszlopvektora, X a f\u00fcggetlen v\u00e1ltoz\u00f3k tervez\u00e9si m\u00e1trixa, X' az X transzpon\u00e1ltja, y pedig a f\u00fcgg\u0151 v\u00e1ltoz\u00f3 megfigyel\u00e9seinek vektora.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-regression-analysis-example\">P\u00e9lda a regresszi\u00f3s elemz\u00e9sre<\/h2>\n\n\n\n<p>Tegy\u00fck fel, hogy az egy\u00e9n tanulm\u00e1nyi \u00e1tlaga (GPA) \u00e9s a heti tanul\u00e1si \u00f3r\u00e1k sz\u00e1ma k\u00f6z\u00f6tti kapcsolatot szeretn\u00e9 megvizsg\u00e1lni. \u00d6sszegy\u0171jti a di\u00e1kok egy csoportj\u00e1r\u00f3l az inform\u00e1ci\u00f3kat, bele\u00e9rtve a tanul\u00f3i \u00f3r\u00e1k sz\u00e1m\u00e1t \u00e9s a tanulm\u00e1nyi \u00e1tlagot.<\/p>\n\n\n\n<p>Ezut\u00e1n a regresszi\u00f3elemz\u00e9s seg\u00edts\u00e9g\u00e9vel megn\u00e9zheti, hogy van-e line\u00e1ris kapcsolat a k\u00e9t v\u00e1ltoz\u00f3 k\u00f6z\u00f6tt, \u00e9s ha igen, akkor l\u00e9trehozhat egy olyan modellt, amely megj\u00f3solja a di\u00e1kok tanulm\u00e1nyi \u00e1tlag\u00e1t a heti tanul\u00f3i \u00f3r\u00e1k sz\u00e1ma alapj\u00e1n.<\/p>\n\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter is-resized\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/lh5.googleusercontent.com\/jY2vs2UsuRYMfVS7ZwPuk_epkVR-Yl7jnG8al1mDmUs6L8YsZ_X3WwNFy40jDCareFFtyOzL6b_DXIhO8FrJR1CMyVwg_rHyE1jycXX-LGWLsUf4LTzWV4L35ObUSidK1EsF136nqG-tHj_zjStgbbA\" alt=\"\" width=\"505\" height=\"263\"\/><figcaption class=\"wp-element-caption\"><em>A k\u00e9p el\u00e9rhet\u0151 a <a href=\"https:\/\/www.alchemer.com\" target=\"_blank\" rel=\"noreferrer noopener\">alchemer.com<\/a><\/em><\/figcaption><\/figure><\/div>\n\n\n<p><a href=\"https:\/\/www.alchemer.com\/wp-content\/uploads\/2019\/04\/regression-analysis-1.png\"><\/a><\/p>\n\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Ha az adatokat sz\u00f3r\u00e1sos t\u00e9rk\u00e9pen \u00e1br\u00e1zoljuk, \u00fagy t\u0171nik, hogy a tanulm\u00e1nyi \u00f3r\u00e1k \u00e9s a tanulm\u00e1nyi \u00e1tlag k\u00f6z\u00f6tt kedvez\u0151 line\u00e1ris kapcsolat van. A legjobb illeszked\u00e9s egyenes\u00e9nek meredeks\u00e9g\u00e9t \u00e9s metsz\u00e9spontj\u00e1t ezut\u00e1n egyszer\u0171 line\u00e1ris regresszi\u00f3s modell seg\u00edts\u00e9g\u00e9vel becs\u00fclj\u00fck meg. A v\u00e9gs\u0151 megold\u00e1s \u00edgy n\u00e9zhet ki:<\/p>\n\n\n\n<p>GPA = 2,0 + 0,3 (heti tanulm\u00e1nyi \u00f3r\u00e1k)<\/p>\n\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter is-resized\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/lh6.googleusercontent.com\/plMkcFRz9dE-xiHm7wkzhCBplbaGIBdvzy4y8LmGqBEaFAMV72IUx7DRx8uvaU_TVMkcOlwcgH_s12NMZFjni4gWrlANjcBH2RqyoFKzrks9q3SGUDpnd_ILZZ4ookIPxD-PJ2T5L-HS3GaWCJf8yEE\" alt=\"\" width=\"505\" height=\"263\"\/><figcaption class=\"wp-element-caption\"><em><em>A k\u00e9p el\u00e9rhet\u0151 a <a href=\"https:\/\/www.alchemer.com\" target=\"_blank\" rel=\"noreferrer noopener\">alchemer.com<\/a><\/em><\/em><\/figcaption><\/figure><\/div>\n\n\n<p><a href=\"https:\/\/www.alchemer.com\/wp-content\/uploads\/2019\/04\/regression-analysis-2.png\"><\/a><\/p>\n\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Ez az egyenlet kimondja, hogy minden heti t\u00f6bblet\u00f3r\u00e1val a tanul\u00f3 tanulm\u00e1nyi \u00e1tlaga 0,3 ponttal emelkedik, minden m\u00e1s egyen\u00e9rt\u00e9k\u0171s\u00e9g mellett. Ez az algoritmus felhaszn\u00e1lhat\u00f3 egy di\u00e1k tanulm\u00e1nyi \u00e1tlag\u00e1nak el\u0151rejelz\u00e9s\u00e9re annak alapj\u00e1n, hogy h\u00e1ny \u00f3r\u00e1t tanul hetente, valamint annak meg\u00e1llap\u00edt\u00e1s\u00e1ra, hogy a tanul\u00e1si rutinjuk alapj\u00e1n mely di\u00e1kokat fenyegeti az alulteljes\u00edt\u00e9s vesz\u00e9lye.&nbsp;<\/p>\n\n\n\n<p>A p\u00e9lda adatainak felhaszn\u00e1l\u00e1s\u00e1val az al\u00e1bbi \u00e9rt\u00e9kek <strong>b<\/strong> \u00e9s <strong>a<\/strong> a k\u00f6vetkez\u0151k:<\/p>\n\n\n\n<p>n = 10 (a megfigyel\u00e9sek sz\u00e1ma)<\/p>\n\n\n\n<p>\u03a3x = 30 (a tanulm\u00e1nyi \u00f3r\u00e1k \u00f6sszege)<\/p>\n\n\n\n<p>\u03a3y = 25 (a GPA-k \u00f6sszege)<\/p>\n\n\n\n<p>\u03a3xy = 149 (a tanulm\u00e1nyi \u00f3r\u00e1k \u00e9s a tanulm\u00e1nyi \u00e1tlagok szorzat\u00e1nak \u00f6sszege)<\/p>\n\n\n\n<p>\u03a3(x)<sup>2<\/sup> = 102 (a tanulm\u00e1nyi \u00f3r\u00e1k n\u00e9gyzet\u00e9nek \u00f6sszege)<\/p>\n\n\n\n<p>Ezen \u00e9rt\u00e9kek felhaszn\u00e1l\u00e1s\u00e1val sz\u00e1m\u00edtsa ki <strong>b<\/strong> mint:<\/p>\n\n\n\n<p>b = (n\u03a3(xy) - \u03a3x\u03a3y) \/ (n\u03a3(x<sup>2<\/sup>) - (\u03a3x)<sup>2<\/sup>)<\/p>\n\n\n\n<p>= (10 * 149 &#8211; 30 * 25) \/ (10 * 102 &#8211; 30<sup>2<\/sup>)<\/p>\n\n\n\n<p>= 0.3<\/p>\n\n\n\n<p>\u00c9s sz\u00e1m\u00edtsa ki <strong>a <\/strong>mint:<\/p>\n\n\n\n<p>a = (\u03a3y - b\u03a3x) \/ n<\/p>\n\n\n\n<p>= (25 &#8211; 0.3 * 30) \/ 10<\/p>\n\n\n\n<p>= 2.0<\/p>\n\n\n\n<p>Ez\u00e9rt a legjobb illeszked\u00e9si egyenes egyenlete a k\u00f6vetkez\u0151:&nbsp;<\/p>\n\n\n\n<p>GPA = 2,0 + 0,3 (heti tanulm\u00e1nyi \u00f3r\u00e1k)<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-what-is-the-difference-between-correlation-and-regression\">Mi a k\u00fcl\u00f6nbs\u00e9g a korrel\u00e1ci\u00f3 \u00e9s a regresszi\u00f3 k\u00f6z\u00f6tt?<\/h2>\n\n\n\n<p>Mind a korrel\u00e1ci\u00f3, mind a regresszi\u00f3 olyan statisztikai m\u00f3dszer, amellyel k\u00e9t v\u00e1ltoz\u00f3 k\u00f6z\u00f6tti kapcsolatot lehet vizsg\u00e1lni. K\u00fcl\u00f6nb\u00f6z\u0151 c\u00e9lokat szolg\u00e1lnak, \u00e9s k\u00fcl\u00f6nb\u00f6z\u0151 t\u00edpus\u00fa inform\u00e1ci\u00f3kat szolg\u00e1ltatnak.<\/p>\n\n\n\n<p>A korrel\u00e1ci\u00f3 a k\u00e9t v\u00e1ltoz\u00f3 k\u00f6z\u00f6tti kapcsolat er\u0151ss\u00e9g\u00e9nek \u00e9s lefoly\u00e1s\u00e1nak m\u00e9r\u0151sz\u00e1ma. A korrel\u00e1ci\u00f3 m\u00e9rt\u00e9ke -1 \u00e9s +1 k\u00f6z\u00f6tt mozog, ahol a -1 a t\u00f6k\u00e9letes negat\u00edv korrel\u00e1ci\u00f3t, a 0 a korrel\u00e1ci\u00f3 hi\u00e1ny\u00e1t, a +1 pedig a t\u00f6k\u00e9letes pozit\u00edv korrel\u00e1ci\u00f3t jelenti. A korrel\u00e1ci\u00f3 azt jelzi, hogy k\u00e9t v\u00e1ltoz\u00f3 milyen m\u00e9rt\u00e9kben kapcsol\u00f3dik egym\u00e1shoz, de nem jelzi az okot vagy a kisz\u00e1m\u00edthat\u00f3s\u00e1got.<\/p>\n\n\n\n<p>A regresszi\u00f3 m\u00e1sr\u00e9szt k\u00e9t v\u00e1ltoz\u00f3 k\u00f6z\u00f6tti kapcsolat modellez\u00e9s\u00e9re szolg\u00e1l\u00f3 m\u00f3dszer, jellemz\u0151en az\u00e9rt, hogy az egyik v\u00e1ltoz\u00f3t a m\u00e1sik alapj\u00e1n el\u0151re jelezz\u00fck vagy magyar\u00e1zzuk. A regresszi\u00f3elemz\u00e9s becsl\u00e9seket adhat a kapcsolat nagys\u00e1g\u00e1r\u00f3l \u00e9s ir\u00e1ny\u00e1r\u00f3l, valamint statisztikai szignifikanciateszteket, konfidencia tartom\u00e1nyokat \u00e9s j\u00f6v\u0151beli eredm\u00e9nyek el\u0151rejelz\u00e9s\u00e9t.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-your-creations-ready-within-minutes\">Az \u00d6n kre\u00e1ci\u00f3i, perceken bel\u00fcl k\u00e9szen \u00e1llnak<\/h2>\n\n\n\n<p><a href=\"https:\/\/mindthegraph.com\" target=\"_blank\" rel=\"noreferrer noopener\">Mind the Graph<\/a> egy olyan online platform, amely tudom\u00e1nyos illusztr\u00e1ci\u00f3k \u00e9s infografikus tervek sz\u00e9les k\u00f6r\u0171 k\u00f6nyvt\u00e1r\u00e1t k\u00edn\u00e1lja, amelyeket egyszer\u0171en m\u00f3dos\u00edthat az egyedi ig\u00e9nyeinek megfelel\u0151en. K\u00e9sz\u00edtsen professzion\u00e1lis megjelen\u00e9s\u0171 grafikonokat, posztereket \u00e9s grafikai \u00f6sszefoglal\u00f3kat percek alatt a drag-and-drop fel\u00fclet, valamint az eszk\u00f6z\u00f6k \u00e9s funkci\u00f3k sz\u00e9les sk\u00e1l\u00e1ja seg\u00edts\u00e9g\u00e9vel.&nbsp;<\/p>\n\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><img decoding=\"async\" loading=\"lazy\" width=\"800\" height=\"500\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/05\/banco.gif\" alt=\"\" class=\"wp-image-28087\"\/><\/figure><\/div>\n\n\n<div style=\"height:21px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<div class=\"is-layout-flex wp-block-buttons\">\n<div class=\"wp-block-button aligncenter\"><a class=\"wp-block-button__link has-background wp-element-button\" href=\"https:\/\/mindthegraph.com\/\" style=\"border-radius:50px;background-color:#dc1866\" target=\"_blank\" rel=\"noreferrer noopener\">Kezdjen alkotni az Mind the Graph-vel<\/a><\/div>\n<\/div>\n\n\n\n<div style=\"height:44px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>","protected":false},"excerpt":{"rendered":"<p>\u00c9rtse meg, hogyan m\u0171k\u00f6dik a regresszi\u00f3elemz\u00e9s egy \u00e1tfog\u00f3 p\u00e9lda seg\u00edts\u00e9g\u00e9vel, \u00e9s ismerje meg a leggyakoribb k\u00e9pleteket. <\/p>","protected":false},"author":28,"featured_media":28437,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[959,28],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Using Regression Analysis to Understand Complex Relationships - Mind the Graph Blog<\/title>\n<meta name=\"description\" content=\"Understand how regression analysis works with ease using a comprehensive example and learn the most common formulas.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/mindthegraph.com\/blog\/hu\/\u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0439\u043d\u0438\u0439-\u0430\u043d\u0430\u043b\u0456\u0437\/\" \/>\n<meta property=\"og:locale\" content=\"hu_HU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Using Regression Analysis to Understand Complex Relationships\" \/>\n<meta property=\"og:description\" content=\"Understand how regression analysis works with ease using a comprehensive example and learn the most common formulas.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/mindthegraph.com\/blog\/hu\/\u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0439\u043d\u0438\u0439-\u0430\u043d\u0430\u043b\u0456\u0437\/\" \/>\n<meta property=\"og:site_name\" content=\"Mind the Graph Blog\" \/>\n<meta property=\"article:published_time\" content=\"2023-06-20T21:17:37+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-07-03T21:36:10+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/07\/regression-analysis-blog.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1124\" \/>\n\t<meta property=\"og:image:height\" content=\"613\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Jessica Abbadia\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:title\" content=\"Using Regression Analysis to Understand Complex Relationships\" \/>\n<meta name=\"twitter:description\" content=\"Understand how regression analysis works with ease using a comprehensive example and learn the most common formulas.\" \/>\n<meta name=\"twitter:image\" content=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/07\/regression-analysis-blog.png\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Jessica Abbadia\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Using Regression Analysis to Understand Complex Relationships - Mind the Graph Blog","description":"Understand how regression analysis works with ease using a comprehensive example and learn the most common formulas.","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:\/\/mindthegraph.com\/blog\/hu\/\u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0439\u043d\u0438\u0439-\u0430\u043d\u0430\u043b\u0456\u0437\/","og_locale":"hu_HU","og_type":"article","og_title":"Using Regression Analysis to Understand Complex Relationships","og_description":"Understand how regression analysis works with ease using a comprehensive example and learn the most common formulas.","og_url":"https:\/\/mindthegraph.com\/blog\/hu\/\u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0439\u043d\u0438\u0439-\u0430\u043d\u0430\u043b\u0456\u0437\/","og_site_name":"Mind the Graph Blog","article_published_time":"2023-06-20T21:17:37+00:00","article_modified_time":"2023-07-03T21:36:10+00:00","og_image":[{"width":1124,"height":613,"url":"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/07\/regression-analysis-blog.png","type":"image\/png"}],"author":"Jessica Abbadia","twitter_card":"summary_large_image","twitter_title":"Using Regression Analysis to Understand Complex Relationships","twitter_description":"Understand how regression analysis works with ease using a comprehensive example and learn the most common formulas.","twitter_image":"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/07\/regression-analysis-blog.png","twitter_misc":{"Written by":"Jessica Abbadia","Est. reading time":"6 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/mindthegraph.com\/blog\/uk\/%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%96%d0%b9%d0%bd%d0%b8%d0%b9-%d0%b0%d0%bd%d0%b0%d0%bb%d1%96%d0%b7\/","url":"https:\/\/mindthegraph.com\/blog\/uk\/%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%96%d0%b9%d0%bd%d0%b8%d0%b9-%d0%b0%d0%bd%d0%b0%d0%bb%d1%96%d0%b7\/","name":"Using Regression Analysis to Understand Complex Relationships - Mind the Graph Blog","isPartOf":{"@id":"https:\/\/mindthegraph.com\/blog\/#website"},"datePublished":"2023-06-20T21:17:37+00:00","dateModified":"2023-07-03T21:36:10+00:00","author":{"@id":"https:\/\/mindthegraph.com\/blog\/#\/schema\/person\/96ecc2d785106e951f7773dc7c96d699"},"description":"Understand how regression analysis works with ease using a comprehensive example and learn the most common formulas.","breadcrumb":{"@id":"https:\/\/mindthegraph.com\/blog\/uk\/%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%96%d0%b9%d0%bd%d0%b8%d0%b9-%d0%b0%d0%bd%d0%b0%d0%bb%d1%96%d0%b7\/#breadcrumb"},"inLanguage":"hu-HU","potentialAction":[{"@type":"ReadAction","target":["https:\/\/mindthegraph.com\/blog\/uk\/%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%96%d0%b9%d0%bd%d0%b8%d0%b9-%d0%b0%d0%bd%d0%b0%d0%bb%d1%96%d0%b7\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/mindthegraph.com\/blog\/uk\/%d1%80%d0%b5%d0%b3%d1%80%d0%b5%d1%81%d1%96%d0%b9%d0%bd%d0%b8%d0%b9-%d0%b0%d0%bd%d0%b0%d0%bb%d1%96%d0%b7\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/mindthegraph.com\/blog\/"},{"@type":"ListItem","position":2,"name":"Using Regression Analysis to Understand Complex Relationships"}]},{"@type":"WebSite","@id":"https:\/\/mindthegraph.com\/blog\/#website","url":"https:\/\/mindthegraph.com\/blog\/","name":"Mind the Graph Blog","description":"Your science can be beautiful!","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/mindthegraph.com\/blog\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"hu-HU"},{"@type":"Person","@id":"https:\/\/mindthegraph.com\/blog\/#\/schema\/person\/96ecc2d785106e951f7773dc7c96d699","name":"Jessica Abbadia","image":{"@type":"ImageObject","inLanguage":"hu-HU","@id":"https:\/\/mindthegraph.com\/blog\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/f477bd20199beb376b04b2fda9a2cec5?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/f477bd20199beb376b04b2fda9a2cec5?s=96&d=mm&r=g","caption":"Jessica Abbadia"},"description":"Jessica Abbadia is a lawyer that has been working in Digital Marketing since 2020, improving organic performance for apps and websites in various regions through ASO and SEO. Currently developing scientific and intellectual knowledge for the community's benefit. Jessica is an animal rights activist who enjoys reading and drinking strong coffee.","sameAs":["https:\/\/www.linkedin.com\/in\/jessica-abbadia-9b834a13b\/"],"url":"https:\/\/mindthegraph.com\/blog\/hu\/author\/jessica\/"}]}},"_links":{"self":[{"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/posts\/28434"}],"collection":[{"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/users\/28"}],"replies":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/comments?post=28434"}],"version-history":[{"count":4,"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/posts\/28434\/revisions"}],"predecessor-version":[{"id":28445,"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/posts\/28434\/revisions\/28445"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/media\/28437"}],"wp:attachment":[{"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/media?parent=28434"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/categories?post=28434"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/hu\/wp-json\/wp\/v2\/tags?post=28434"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}