{"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\/lv\/regresijas-analize\/","title":{"rendered":"Regresijas anal\u012bzes izmanto\u0161ana, lai izprastu sare\u017e\u0123\u012btas attiec\u012bbas"},"content":{"rendered":"<p>Regresijas anal\u012bze ir pieeja, ar kuras pal\u012bdz\u012bbu nosaka un analiz\u0113 saist\u012bbu starp vienu vai vair\u0101kiem neatkar\u012bgajiem main\u012bgajiem un atkar\u012bgo main\u012bgo. \u0160o metodi pla\u0161i izmanto da\u017e\u0101d\u0101s discipl\u012bn\u0101s, tostarp vesel\u012bbas apr\u016bp\u0113, soci\u0101laj\u0101s zin\u0101tn\u0113s, in\u017eenierzin\u0101tn\u0113s, ekonomik\u0101 un uz\u0146\u0113m\u0113jdarb\u012bb\u0101. J\u016bs varat izmantot regresijas anal\u012bzi, lai izp\u0113t\u012btu fundament\u0101las datu sakar\u012bbas un izstr\u0101d\u0101tu prognoz\u0113\u0161anas mode\u013cus, kas pal\u012bdz\u0113s jums pie\u0146emt pamatotus l\u0113mumus.<\/p>\n\n\n\n<p>\u0160aj\u0101 rakst\u0101 sniegts visaptvero\u0161s regresijas anal\u012bzes p\u0101rskats, tostarp t\u0101s darb\u012bbas principi, viegli saprotams piem\u0113rs, k\u0101 ar\u012b paskaidrots, ar ko t\u0101 at\u0161\u0137iras no korel\u0101cijas anal\u012bzes.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-what-is-regression-analysis\">Kas ir regresijas anal\u012bze?<\/h2>\n\n\n\n<p>Regresijas anal\u012bze ir statistikas metode, ar kuras pal\u012bdz\u012bbu nosaka un kvantitat\u012bvi nosaka saist\u012bbu starp atkar\u012bgo main\u012bgo un vienu vai vair\u0101kiem neatkar\u012bgajiem main\u012bgajiem. \u012as\u0101k sakot, t\u0101 pal\u012bdz saprast, k\u0101 izmai\u0146as vien\u0101 vai vair\u0101kos neatkar\u012bgajos main\u012bgajos ir saist\u012btas ar izmai\u0146\u0101m atkar\u012bgaj\u0101 main\u012bgaj\u0101.<\/p>\n\n\n\n<p>Lai g\u016btu padzi\u013cin\u0101tu izpratni par regresijas anal\u012bzi, vispirms ir j\u0101izprot \u0161\u0101di termini:<\/p>\n\n\n\n<ul>\n<li><strong>Atkar\u012bgais main\u012bgais: <\/strong>Tas ir main\u012bgais lielums, kuru j\u016bs v\u0113laties analiz\u0113t vai prognoz\u0113t. Tas ir izn\u0101kuma main\u012bgais lielums, kuru j\u016bs m\u0113\u0123in\u0101t saprast un izskaidrot.<\/li>\n\n\n\n<li><strong>Neatkar\u012bgie main\u012bgie: <\/strong>Tie ir main\u012bgie lielumi, kas, j\u016bsupr\u0101t, ietekm\u0113 atkar\u012bgo main\u012bgo lielumu. Tos bie\u017ei d\u0113v\u0113 par prognoz\u0113jo\u0161ajiem main\u012bgajiem, jo tie tiek izmantoti, lai prognoz\u0113tu vai izskaidrotu atkar\u012bg\u0101 main\u012bg\u0101 izmai\u0146as.<\/li>\n<\/ul>\n\n\n\n<p>Regresijas anal\u012bzi var izmantot da\u017e\u0101dos gad\u012bjumos, tostarp atkar\u012bg\u0101 main\u012bg\u0101 lieluma n\u0101kotnes v\u0113rt\u012bbu prognoz\u0113\u0161anai, neatkar\u012bgo main\u012bgo lielumu ietekmes uz atkar\u012bgo main\u012bgo izpratnei un novir\u017eu vai neparastu par\u0101d\u012bbu atkl\u0101\u0161anai datu v\u0101k\u0161an\u0101.<\/p>\n\n\n\n<p>Regresijas anal\u012bzi var iedal\u012bt vair\u0101kos veidos, tostarp vienk\u0101r\u0161\u0101 line\u0101r\u0101 regresija, lo\u0123isk\u0101 regresija, polinomisk\u0101 regresija un daudzk\u0101rt\u0113j\u0101 regresija. Piem\u0113roto regresijas modeli nosaka atkar\u012bb\u0101 no datu rakstura un apl\u016bkojam\u0101 p\u0113t\u012bjuma priek\u0161meta.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-how-does-regression-analysis-work\">K\u0101 darbojas regresijas anal\u012bze?<\/h2>\n\n\n\n<p>Regresijas anal\u012bzes m\u0113r\u0137is ir noteikt vispiem\u0113rot\u0101ko l\u012bniju vai l\u012bkni, kas atspogu\u013co saist\u012bbu starp neatkar\u012bgajiem main\u012bgajiem un atkar\u012bgo main\u012bgo. \u0160o vispiem\u0113rot\u0101ko l\u012bniju vai l\u012bkni \u0123ener\u0113, izmantojot statistikas metodes, kas samazina at\u0161\u0137ir\u012bbas starp sagaid\u0101maj\u0101m un re\u0101laj\u0101m v\u0113rt\u012bb\u0101m datu kop\u0101.<\/p>\n\n\n\n<p>\u0160eit ir sniegtas divu visbie\u017e\u0101k sastopamo regresijas anal\u012bzes veidu formulas:<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-single-linear-regression\">Viena line\u0101r\u0101 regresija<\/h3>\n\n\n\n<p>Vienk\u0101r\u0161aj\u0101 line\u0101raj\u0101 regresij\u0101, lai par\u0101d\u012btu sakar\u012bbu starp diviem main\u012bgajiem lielumiem: neatkar\u012bgo main\u012bgo (x) un atkar\u012bgo main\u012bgo (y), tiek izmantota l\u012bnija, kas vislab\u0101k atbilst.<\/p>\n\n\n\n<p>Vislab\u0101k atbilst\u012bgo l\u012bniju var att\u0113lot ar vien\u0101dojumu: y = a + bx.<\/p>\n\n\n\n<p>\u0160eit a ir p\u0101rtver\u0161anas punkts, b ir l\u012bnijas sl\u012bpums. Lai apr\u0113\u0137in\u0101tu sl\u012bpumu, izmanto formulu: b = (n\u03a3(xy) - \u03a3x\u03a3y) \/ (n\u03a3(x<sup>2<\/sup>) - (\u03a3x)<sup>2<\/sup>), kur n ir nov\u0113rojumu skaits, \u03a3xy ir x un y reizin\u0101juma summa, \u03a3x un \u03a3y ir attiec\u012bgi x un y summas, un \u03a3(x<sup>2<\/sup>) ir x kvadr\u0101tu summa.<\/p>\n\n\n\n<p>Lai apr\u0113\u0137in\u0101tu intercepciju, izmanto formulu: a = (\u03a3y - b\u03a3x) \/ n.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-multiple-regression\">Vair\u0101kk\u0101rt\u0113ja regresija&nbsp;<\/h3>\n\n\n\n<p>Vair\u0101kk\u0101rt\u0113ja line\u0101r\u0101 regresija:<\/p>\n\n\n\n<p>Daudzk\u0101rt\u0113j\u0101s line\u0101r\u0101s regresijas mode\u013ca vien\u0101dojuma formula ir \u0161\u0101da:<\/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>kur y ir atkar\u012bgais main\u012bgais, x<sub>1<\/sub>, x<sub>2<\/sub>, ..., x<sub>n<\/sub> ir neatkar\u012bgie main\u012bgie, un b<sub>0<\/sub>, b<sub>1<\/sub>, b<sub>2<\/sub>, ..., bn ir neatkar\u012bgo main\u012bgo koeficienti.<\/p>\n\n\n\n<p>Koeficientu nov\u0113rt\u0113\u0161anas formula, izmantojot parasto maz\u0101ko kvadr\u0101tu metodi, ir \u0161\u0101da:<\/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>kur \u03b2 ir koeficientu kolonnas vektors, X ir neatkar\u012bgo main\u012bgo konstrukcijas matrica, X' ir X transpoz\u012bcija un y ir atkar\u012bg\u0101 main\u012bg\u0101 nov\u0113rojumu vektors.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-regression-analysis-example\">Regresijas anal\u012bzes piem\u0113rs<\/h2>\n\n\n\n<p>Pie\u0146emsim, ka v\u0113laties izp\u0113t\u012bt saist\u012bbu starp indiv\u012bda vid\u0113jo v\u0113rt\u0113jumu (GPA) un stundu skaitu, ko vi\u0146\u0161 ned\u0113\u013c\u0101 m\u0101c\u0101s. J\u016bs apkopojat inform\u0101ciju no studentu kopas, ieskaitot vi\u0146u m\u0101c\u012bbu stundu skaitu un vid\u0113jo v\u0113rt\u0113jumu.<\/p>\n\n\n\n<p>P\u0113c tam ar regresijas anal\u012bzes pal\u012bdz\u012bbu noskaidrojiet, vai starp abiem main\u012bgajiem ir line\u0101ra sakar\u012bba, un, ja ir, varat izveidot modeli, kas paredz skol\u0113na GPA, pamatojoties uz m\u0101c\u012bbu stundu skaitu ned\u0113\u013c\u0101.<\/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>Att\u0113ls pieejams <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>Ja datus att\u0113lo izkliedes kart\u0113, redzams, ka past\u0101v labv\u0113l\u012bga line\u0101ra sakar\u012bba starp m\u0101c\u012bbu stund\u0101m un GPA. P\u0113c tam, izmantojot vienk\u0101r\u0161u line\u0101r\u0101s regresijas modeli, tiek nov\u0113rt\u0113ts lab\u0101k\u0101s atbilst\u012bbas l\u012bnijas sl\u012bpums un krustpunkts. Gal\u012bgais risin\u0101jums var\u0113tu izskat\u012bties \u0161\u0101di:<\/p>\n\n\n\n<p>GPA = 2,0 + 0,3 (m\u0101c\u012bbu stundas ned\u0113\u013c\u0101)<\/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>Att\u0113ls pieejams <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>\u0160is vien\u0101dojums nosaka, ka par katru papildu m\u0101c\u012bbu stundu ned\u0113\u013c\u0101 studenta GPA palielin\u0101sies par 0,3 punktiem, bet viss p\u0101r\u0113jais ir l\u012bdzv\u0113rt\u012bgs. \u0160o algoritmu var izmantot, lai prognoz\u0113tu studenta GPA, pamatojoties uz to, cik stundu ned\u0113\u013c\u0101 vi\u0146\u0161 m\u0101c\u0101s, k\u0101 ar\u012b lai noteiktu, kuriem studentiem ir risks, ka vi\u0146u m\u0101c\u012bbu rut\u012bnas d\u0113\u013c vi\u0146i uzr\u0101d\u012bs slikt\u0101kus rezult\u0101tus.&nbsp;<\/p>\n\n\n\n<p>Izmantojot piem\u0113r\u0101 sniegtos datus, v\u0113rt\u012bbas <strong>b<\/strong> un <strong>a<\/strong> ir \u0161\u0101di:<\/p>\n\n\n\n<p>n = 10 (nov\u0113rojumu skaits)<\/p>\n\n\n\n<p>\u03a3x = 30 (m\u0101c\u012bbu stundu summa)<\/p>\n\n\n\n<p>\u03a3y = 25 (GPA summa)<\/p>\n\n\n\n<p>\u03a3xy = 149 (studiju stundu un GPA reizin\u0101juma summa)<\/p>\n\n\n\n<p>\u03a3(x)<sup>2<\/sup> = 102 (m\u0101c\u012bbu stundu kvadr\u0101tu summa)<\/p>\n\n\n\n<p>Izmantojot \u0161\u012bs v\u0113rt\u012bbas, apr\u0113\u0137iniet <strong>b<\/strong> k\u0101:<\/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>Un apr\u0113\u0137iniet <strong>a <\/strong>k\u0101:<\/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>T\u0101p\u0113c vislab\u0101k\u0101s atbilst\u012bbas l\u012bnijas vien\u0101dojums ir:&nbsp;<\/p>\n\n\n\n<p>GPA = 2,0 + 0,3 (m\u0101c\u012bbu stundas ned\u0113\u013c\u0101)<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-what-is-the-difference-between-correlation-and-regression\">K\u0101da ir at\u0161\u0137ir\u012bba starp korel\u0101ciju un regresiju?<\/h2>\n\n\n\n<p>Gan korel\u0101cija, gan regresija ir statistikas metodes, ar kur\u0101m p\u0101rbauda saikni starp diviem main\u012bgajiem. T\u0101s kalpo da\u017e\u0101diem m\u0113r\u0137iem un sniedz da\u017e\u0101da veida inform\u0101ciju.<\/p>\n\n\n\n<p>Korel\u0101cija ir divu main\u012bgo lielumu savstarp\u0113j\u0101s saiknes stipruma un gaitas m\u0113rs. T\u0101 vari\u0113 no -1 l\u012bdz +1, kur -1 ir piln\u012bga negat\u012bva korel\u0101cija, 0 ir bez korel\u0101cijas, bet +1 ir piln\u012bga pozit\u012bva korel\u0101cija. Korel\u0101cija nor\u0101da, cik liel\u0101 m\u0113r\u0101 divi main\u012bgie ir saist\u012bti, bet t\u0101 nenor\u0101da c\u0113loni vai prognoz\u0113jam\u012bbu.<\/p>\n\n\n\n<p>Savuk\u0101rt regresija ir metode, ar kuru model\u0113 saikni starp diviem main\u012bgajiem lielumiem, parasti, lai prognoz\u0113tu vai izskaidrotu vienu main\u012bgo, pamatojoties uz otru. Regresijas anal\u012bze var sniegt apl\u0113ses par saist\u012bbas lielumu un virzienu, k\u0101 ar\u012b statistisk\u0101 noz\u012bm\u012bguma testus, ticam\u012bbas diapazonus un n\u0101kotnes rezult\u0101tu prognozes.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-your-creations-ready-within-minutes\">J\u016bsu darbi, gatavi da\u017eu min\u016b\u0161u laik\u0101<\/h2>\n\n\n\n<p><a href=\"https:\/\/mindthegraph.com\" target=\"_blank\" rel=\"noreferrer noopener\">Mind the Graph<\/a> ir tie\u0161saistes platforma, kas pied\u0101v\u0101 pla\u0161u zin\u0101tnisko ilustr\u0101ciju un infografikas dizainu bibliot\u0113ku, ko var vienk\u0101r\u0161i p\u0101rveidot atbilsto\u0161i j\u016bsu unik\u0101laj\u0101m vajadz\u012bb\u0101m. Izveidojiet profesion\u0101la izskata diagrammas, plak\u0101tus un grafiskus kopsavilkumus da\u017eu min\u016b\u0161u laik\u0101, izmantojot vilk\u0161anas un nome\u0161anas saskarni un pla\u0161u r\u012bku un funkciju kl\u0101stu.&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\">S\u0101ciet veidot ar Mind the Graph<\/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>Izprotiet, k\u0101 regresijas anal\u012bze darbojas, izmantojot visaptvero\u0161u piem\u0113ru, un apg\u016bstiet visbie\u017e\u0101k sastopam\u0101s formulas. <\/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\/lv\/\u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0439\u043d\u0438\u0439-\u0430\u043d\u0430\u043b\u0456\u0437\/\" \/>\n<meta property=\"og:locale\" content=\"lv_LV\" \/>\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\/lv\/\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\/lv\/\u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0439\u043d\u0438\u0439-\u0430\u043d\u0430\u043b\u0456\u0437\/","og_locale":"lv_LV","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\/lv\/\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":"lv","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":"lv"},{"@type":"Person","@id":"https:\/\/mindthegraph.com\/blog\/#\/schema\/person\/96ecc2d785106e951f7773dc7c96d699","name":"Jessica Abbadia","image":{"@type":"ImageObject","inLanguage":"lv","@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\/lv\/author\/jessica\/"}]}},"_links":{"self":[{"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/posts\/28434"}],"collection":[{"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/users\/28"}],"replies":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/comments?post=28434"}],"version-history":[{"count":4,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/posts\/28434\/revisions"}],"predecessor-version":[{"id":28445,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/posts\/28434\/revisions\/28445"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/media\/28437"}],"wp:attachment":[{"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/media?parent=28434"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/categories?post=28434"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/tags?post=28434"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}