{"id":28669,"date":"2023-07-18T10:31:35","date_gmt":"2023-07-18T13:31:35","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/scientific-prediction-copy\/"},"modified":"2023-07-18T10:37:02","modified_gmt":"2023-07-18T13:37:02","slug":"extraneous-variables","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/lv\/arejie-mainigie\/","title":{"rendered":"\u0100r\u0113jie main\u012bgie p\u0113t\u012bjumos: Potenci\u0101l\u0101s ietekmes regul\u0113\u0161ana"},"content":{"rendered":"<p>Main\u012bgo lielumu kontrole ir b\u016btiska zin\u0101tniskajos p\u0113t\u012bjumos, lai nodro\u0161in\u0101tu rezult\u0101tu der\u012bgumu un ticam\u012bbu. Tom\u0113r pat visprec\u012bz\u0101k sagatavotos p\u0113t\u012bjumus var ietekm\u0113t \u0101r\u0113ji main\u012bgie lielumi, ar kuriem nav m\u0113r\u0137tiec\u012bgi manipul\u0113ts vai kuri nav \u0146emti v\u0113r\u0101, bet kuri tom\u0113r var ietekm\u0113t p\u0113t\u012bjuma secin\u0101jumus. \u0100r\u0113jie main\u012bgie var veicin\u0101t nepareizu rezult\u0101tu ieg\u016b\u0161anu, sliktas prognozes un p\u0113t\u012bjumu atk\u0101rtojam\u012bbas tr\u016bkumu.&nbsp;<\/p>\n\n\n\n<p>\u0160aj\u0101 rakst\u0101 apl\u016bkosim visu b\u016btisko inform\u0101ciju par \u0101r\u0113jiem main\u012bgajiem lielumiem, k\u0101p\u0113c tie ir svar\u012bgi un ar k\u0101diem var saskarties, veicot p\u0113t\u012bjumu.&nbsp;<\/p>\n\n\n\n<h2 id=\"h-what-are-extraneous-variables\">Kas ir \u0101r\u0113jie main\u012bgie?<\/h2>\n\n\n\n<p>Sve\u0161s main\u012bgais lielums ir main\u012bgais lielums, ar kuru zin\u0101tniskaj\u0101 p\u0113t\u012bjum\u0101 netiek m\u0113r\u0137tiec\u012bgi manipul\u0113ts vai kur\u0161 netiek kontrol\u0113ts, bet kur\u0161 tom\u0113r var ietekm\u0113t p\u0113t\u012bjuma secin\u0101jumus. Tie var sajaukt vai izkrop\u013cot main\u012bgos lielumus, galvenok\u0101rt ietekm\u0113jot atkar\u012bgo(-os) main\u012bgo(-os).<\/p>\n\n\n\n<p>Tas var apdraud\u0113t p\u0113t\u012bjuma der\u012bgumu un mazin\u0101t sp\u0113ju izdar\u012bt atbilsto\u0161us secin\u0101jumus vai izdar\u012bt pla\u0161us visp\u0101rin\u0101jumus, pamatojoties uz ieg\u016btajiem rezult\u0101tiem. Lai nodro\u0161in\u0101tu savu secin\u0101jumu ticam\u012bbu un der\u012bgumu, p\u0113tniekiem r\u016bp\u012bgi j\u0101analiz\u0113 un j\u0101kontrol\u0113 \u0101r\u0113jie main\u012bgie.<\/p>\n\n\n\n<p>\u0100r\u0113jie main\u012bgie lielumi var rasties vair\u0101ku iemeslu d\u0113\u013c, tostarp dal\u012bbnieku at\u0161\u0137ir\u012bbu, eksperiment\u0101l\u0101s vides vai apst\u0101k\u013cu izmai\u0146u un nekontrol\u0113tas vides ietekmes d\u0113\u013c.&nbsp;<\/p>\n\n\n\n<h2 id=\"h-why-are-extraneous-variables-important\">K\u0101p\u0113c ir svar\u012bgi sve\u0161ie main\u012bgie?<\/h2>\n\n\n\n<p>\u0100r\u0113jie main\u012bgie ir svar\u012bgi, jo tie var b\u016btiski ietekm\u0113t zin\u0101tnisk\u0101 p\u0113t\u012bjuma rezult\u0101tu, iesp\u0113jams, izkrop\u013cojot un ietekm\u0113jot atkar\u012bgo(-os) main\u012bgo(-os).&nbsp;<\/p>\n\n\n\n<p>K\u0101 min\u0113ts iepriek\u0161, \u0101r\u0113jie main\u012bgie var rad\u012bt k\u013c\u016bdainus vai maldino\u0161us rezult\u0101tus, ja tie netiek identific\u0113ti un \u0146emti v\u0113r\u0101, kas var b\u016btiski ietekm\u0113t turpm\u0101kos p\u0113t\u012bjumus un re\u0101lo lietojumu.<\/p>\n\n\n\n<p>\u0100r\u0113jie main\u012bgie var rad\u012bt novirzes, piem\u0113ram:<\/p>\n\n\n\n<ul>\n<li><strong>Izsl\u0113g\u0161anas novirze:<\/strong> Tas notiek, ja p\u0113t\u012bjuma dal\u012bbnieki, kas izst\u0101jas, sistem\u0101tiski at\u0161\u0137iras no tiem, kas paliek;<\/li>\n\n\n\n<li><strong>Nepiln\u012bga sl\u0113p\u0161anas aizspriedumain\u012bba: <\/strong>Gad\u0101s, ja izlas\u0113 nav p\u0101rst\u0101v\u0113ts k\u0101ds konkr\u0113ts popul\u0101cijas indiv\u012bds;<\/li>\n\n\n\n<li><strong>Neatbildes novirze:<\/strong> Tas notiek, ja tie, kas neatbild uz aptaujas jaut\u0101jumiem, iev\u0113rojami at\u0161\u0137iras no tiem, kas atbild uz aptaujas jaut\u0101jumiem;<\/li>\n\n\n\n<li><a href=\"https:\/\/mindthegraph.com\/blog\/sampling-bias\/\"><strong>Paraugu atlases novirze<\/strong><\/a><strong>, kas paz\u012bstama ar\u012b k\u0101 noskaidro\u0161anas novirze:<\/strong> Tas notiek, ja da\u017ei m\u0113r\u0137a grupas locek\u013ci ir maz\u0101k ieinteres\u0113ti nek\u0101 citi;<\/li>\n\n\n\n<li><strong>izdz\u012bvo\u0161anas tendence:<\/strong> Tas notiek tad, kad p\u0113tnieki konstat\u0113 secin\u0101jumus, pamatojoties tikai uz veiksm\u012bgu cilv\u0113ku gad\u012bjumiem, nevis uz visu grupu.<\/li>\n<\/ul>\n\n\n\n<p>P\u0113tnieki var pal\u012bdz\u0113t nodro\u0161in\u0101t savu secin\u0101jumu der\u012bgumu un ticam\u012bbu, pareizi identific\u0113jot un kori\u0123\u0113jot \u0101r\u0113jos main\u012bgos. Tas noz\u012bm\u0113 samazin\u0101t vai nov\u0113rst sve\u0161u main\u012bgo ietekmi, izmantojot eksperiment\u0101lo pl\u0101nu (piem\u0113ram, nejau\u0161\u012bbas principa noteik\u0161anu, l\u012bdzsvaro\u0161anu) vai statistisko anal\u012bzi. (piem\u0113ram, iek\u013caujot sve\u0161us main\u012bgos k\u0101 kovari\u0101tus). P\u0113tnieki, \u0161\u0101di r\u012bkojoties, var palielin\u0101t savu uztic\u012bbu p\u0113t\u012bjuma rezult\u0101tiem un sniegt zin\u0101tniskajai sabiedr\u012bbai prec\u012bz\u0101ku un v\u0113rt\u012bg\u0101ku inform\u0101ciju.<\/p>\n\n\n\n<h2 id=\"h-what-are-the-types-of-extraneous-variables\">K\u0101di ir \u0101r\u0113jo main\u012bgo veidi?<\/h2>\n\n\n\n<p>Past\u0101v da\u017e\u0101da veida \u0101r\u0113jie main\u012bgie, kas, iesp\u0113jams, var ietekm\u0113t zin\u0101tnisk\u0101 p\u0113t\u012bjuma rezult\u0101tus. \u0160ie ir da\u017ei piem\u0113ri:<\/p>\n\n\n\n<h3 id=\"h-demand-characteristics-variable\">Piepras\u012bjuma raksturlielumu main\u012bgais lielums<\/h3>\n\n\n\n<p>Sve\u0161a main\u012bg\u0101 lieluma veids, kas rodas, kad p\u0113t\u012bjuma dal\u012bbnieki maina savu uzved\u012bbu vai reakcijas, \u0146emot v\u0113r\u0101 pa\u0161a eksperimenta sniegt\u0101s nor\u0101des vai gaidas. Piem\u0113ram, ja dal\u012bbnieki j\u016bt, ka no vi\u0146iem sagaida noteiktu uzved\u012bbu vai reakciju, vi\u0146i var attiec\u012bgi piel\u0101got savu uzved\u012bbu.<\/p>\n\n\n\n<h3 id=\"h-situational-variables\">Situ\u0101cijas main\u012bgie lielumi<\/h3>\n\n\n\n<p>\u0160ie<strong> <\/strong>ir \u0101r\u0113jie main\u012bgie lielumi, kas rodas eksperiment\u0101l\u0101s vides vai vides elementu d\u0113\u013c. Piem\u0113ram, temperat\u016bras, apgaismojuma vai trok\u0161\u0146a l\u012bme\u0146a izmai\u0146as var ietekm\u0113t p\u0113t\u012bjuma rezult\u0101tus, t\u0101pat k\u0101 citu personu kl\u0101tb\u016btne vai trauc\u0113jo\u0161i faktori apk\u0101rt\u0113j\u0101 vid\u0113.<\/p>\n\n\n\n<h3 id=\"h-participant-variables\">Dal\u012bbnieku main\u012bgie lielumi<\/h3>\n\n\n\n<p>Individu\u0101l\u0101s at\u0161\u0137ir\u012bbas starp dal\u012bbniekiem, kas, ja netiek \u0146emtas v\u0113r\u0101, var ietekm\u0113t p\u0113t\u012bjuma rezult\u0101tus. Var \u0146emt v\u0113r\u0101 gan demogr\u0101fisk\u0101s, piem\u0113ram, vecumu, dzimumu un etnisko pieder\u012bbu, gan psiholo\u0123isk\u0101s, piem\u0113ram, person\u012bbas iez\u012bmes, kognit\u012bv\u0101s sp\u0113jas vai garast\u0101vokli.<\/p>\n\n\n\n<h3 id=\"h-experimenter-variable\">Eksperiment\u0113t\u0101ja main\u012bgais lielums<\/h3>\n\n\n\n<p>Eksperiment\u0113t\u0101ja main\u012bgie lielumi ir iedal\u012bti div\u0101s kategorij\u0101s. Pirm\u0101 ir t\u0101, ka eksperiment\u0113t\u0101ju mijiedarb\u012bba ar dal\u012bbniekiem var net\u012b\u0161i ietekm\u0113t vi\u0146u uzved\u012bbu, kas ir analogs piepras\u012bjuma raksturlielumu main\u012bgajam. Otrais faktors ir iesp\u0113jam\u0101 eksperiment\u0113t\u0101ja rad\u012bt\u0101 neobjektivit\u0101te m\u0113r\u012bjumos, nov\u0113rojumos, anal\u012bz\u0113 vai interpret\u0101cij\u0101, kas var main\u012bt p\u0113t\u012bjuma rezult\u0101tus.<\/p>\n\n\n\n<h3 id=\"h-methodological-variables\">Metodolo\u0123iskie main\u012bgie lielumi<\/h3>\n\n\n\n<p>P\u0113t\u012bjuma tehnikas vai procesu vari\u0101cijas, piem\u0113ram, novirzes m\u0113r\u012b\u0161anas iek\u0101rt\u0101s vai datu v\u0101k\u0161anas metod\u0113s, var b\u016bt \u0101r\u0113ji main\u012bgie lielumi, kas ietekm\u0113 secin\u0101jumus.<\/p>\n\n\n\n<h3 id=\"h-time-variables\">Laika main\u012bgie<\/h3>\n\n\n\n<p>Laika main\u012bgie lielumi, piem\u0113ram, diennakts laiks vai ned\u0113\u013cas diena, var b\u016bt \u0101r\u0113ji faktori, kas ietekm\u0113 p\u0113t\u012bjuma rezult\u0101tus.<\/p>\n\n\n\n<h3 id=\"h-task-variables\">Uzdevuma main\u012bgie<\/h3>\n\n\n\n<p>P\u0113t\u012bjum\u0101 izmantot\u0101 uzdevuma vai stimula raksturojums, piem\u0113ram, t\u0101 sare\u017e\u0123\u012bt\u012bba vai paz\u012bstam\u012bba, var b\u016bt \u0101r\u0113ji main\u012bgie lielumi, kas ietekm\u0113 p\u0113t\u012bjuma rezult\u0101tus.<\/p>\n\n\n\n<h2 id=\"h-how-to-control-extraneous-variables\">K\u0101 kontrol\u0113t sve\u0161us main\u012bgos?<\/h2>\n\n\n\n<p>\u0160eit ir da\u017ei vienk\u0101r\u0161i pas\u0101kumi, ko p\u0113tnieki var veikt, lai kontrol\u0113tu nekontrol\u0113jamus main\u012bgos lielumus:<\/p>\n\n\n\n<h3>1. Identific\u0113t iesp\u0113jamos nevajadz\u012bgos main\u012bgos lielumus<\/h3>\n\n\n\n<p>P\u0113tniekiem r\u016bp\u012bgi j\u0101analiz\u0113 visi iesp\u0113jamie faktori, kas var\u0113tu ietekm\u0113t p\u0113t\u012bjuma rezult\u0101tus, un j\u0101identific\u0113 tie faktori, kas ir sve\u0161i.<\/p>\n\n\n\n<h3>2. Kontroles metode<\/h3>\n\n\n\n<p>Kad esat identific\u0113jis \u0101r\u0113jos main\u012bgos, kas ietekm\u0113 j\u016bsu p\u0113t\u012bjumu, varat izv\u0113l\u0113ties kontroles metodi. Metodes ir saist\u012btas ar noteiktu main\u012bgo kategoriju, t\u0101p\u0113c ir vienk\u0101r\u0161i izv\u0113l\u0113ties, kuru metodi piem\u0113rot. Kontroles metodes ir \u0161\u0101das:<\/p>\n\n\n\n<h4 id=\"h-standardized-procedures\">Standartiz\u0113tas proced\u016bras<\/h4>\n\n\n\n<p>\u0160\u012b pieeja attiecas uz situ\u0101cijas, laika, uzdevuma un piepras\u012bjuma main\u012bgajiem raksturlielumiem, kas par\u0101d\u0101s vis\u0101 p\u0113t\u012bjuma gait\u0101. Izveidojiet standarta m\u0113r\u012bjumus, lai nodro\u0161in\u0101tu konsekventu vidi visiem dal\u012bbniekiem.<\/p>\n\n\n\n<h4 id=\"h-counterbalancing\">L\u012bdzsvars<\/h4>\n\n\n\n<p>\u0160\u012b pieeja ir saist\u012bta ar dal\u012bbnieku main\u012bgajiem lielumiem, piem\u0113ram, p\u0113t\u012bjuma \u012bpa\u0161o notikumu sec\u012bbu. Lai to \u0146emtu v\u0113r\u0101, vienai dal\u012bbnieku grupai var uzdot pabeigt k\u0101du sada\u013cu, kam\u0113r cita grupa pabeidz citu sada\u013cu.<\/p>\n\n\n\n<h4 id=\"h-random-sampling\">Izlases veido\u0161ana izlases veid\u0101<\/h4>\n\n\n\n<p>\u0160\u012b pieeja ir saist\u012bta ar dal\u012bbnieku main\u012bgajiem lielumiem un nodro\u0161ina, ka visiem dal\u012bbniekiem ir vien\u0101da varb\u016bt\u012bba tikt izv\u0113l\u0113tiem. Piem\u0113ram, sadalot cilv\u0113kus kontroles grup\u0101 un eksperiment\u0101laj\u0101 grup\u0101, j\u016bs varat izloz\u0113t v\u0101rdus p\u0113c nejau\u0161\u012bbas principa, lai nodro\u0161in\u0101tu, ka katram indiv\u012bdam ir vien\u0101das iesp\u0113jas b\u016bt k\u0101d\u0101 no grup\u0101m.<\/p>\n\n\n\n<h4 id=\"h-masking\">Mask\u0113\u0161ana<\/h4>\n\n\n\n<p>\u0160\u012b pieeja attiecas uz eksperiment\u0113t\u0101ja main\u012bgajiem lielumiem. Mask\u0113\u0161ana noz\u012bm\u0113, ka eksperimentu veic k\u0101ds, kas nezina p\u0113t\u012bjuma m\u0113r\u0137i.<\/p>\n\n\n\n<h2 id=\"h-the-world-s-largest-scientifically-accurate-illustrations-gallery\">Pasaul\u0113 liel\u0101k\u0101 zin\u0101tniski prec\u012bzu ilustr\u0101ciju galerija<\/h2>\n\n\n\n<p><a href=\"https:\/\/mindthegraph.com\" target=\"_blank\" rel=\"noreferrer noopener\">Mind the Graph<\/a> ir pasaul\u0113 liel\u0101k\u0101 zin\u0101tniski prec\u012bzu ilustr\u0101ciju galerija, kur\u0101 ir ilustr\u0101cijas un grafiki no daudz\u0101m zin\u0101tnes nozar\u0113m, piem\u0113ram, biolo\u0123ijas, \u0137\u012bmijas, fizikas un cit\u0101m. Vienk\u0101r\u0161i lietojams un fantastiski uzlabo j\u016bsu darba kvalit\u0101ti!<\/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=\"600\" height=\"394\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2022\/12\/3yuqz9n9m78.gif\" alt=\"\" class=\"wp-image-25763\"\/><\/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>Uzziniet vair\u0101k par sve\u0161iem main\u012bgajiem lielumiem p\u0113t\u012bjumos un veidiem, k\u0101 tos kontrol\u0113t, lai palielin\u0101tu p\u0113t\u012bjuma iek\u0161\u0113jo der\u012bgumu.<\/p>","protected":false},"author":28,"featured_media":28672,"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>Extraneous Variables in Research: Regulating Potential Influences - Mind the Graph Blog<\/title>\n<meta name=\"description\" content=\"Learn about extraneous variables in research and ways for controlling them to increase the internal validity of your research.\" \/>\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\/variables-extranas\/\" \/>\n<meta property=\"og:locale\" content=\"lv_LV\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Extraneous Variables in Research: Regulating Potential Influences\" \/>\n<meta property=\"og:description\" content=\"Learn about extraneous variables in research and ways for controlling them to increase the internal validity of your research.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/mindthegraph.com\/blog\/lv\/variables-extranas\/\" \/>\n<meta property=\"og:site_name\" content=\"Mind the Graph Blog\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-18T13:31:35+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-07-18T13:37:02+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/07\/extraneous-variables-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=\"Extraneous Variables in Research: Regulating Potential Influences\" \/>\n<meta name=\"twitter:description\" content=\"Learn about extraneous variables in research and ways for controlling them to increase the internal validity of your research.\" \/>\n<meta name=\"twitter:image\" content=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/07\/extraneous-variables-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=\"5 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Extraneous Variables in Research: Regulating Potential Influences - Mind the Graph Blog","description":"Learn about extraneous variables in research and ways for controlling them to increase the internal validity of your research.","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\/variables-extranas\/","og_locale":"lv_LV","og_type":"article","og_title":"Extraneous Variables in Research: Regulating Potential Influences","og_description":"Learn about extraneous variables in research and ways for controlling them to increase the internal validity of your research.","og_url":"https:\/\/mindthegraph.com\/blog\/lv\/variables-extranas\/","og_site_name":"Mind the Graph Blog","article_published_time":"2023-07-18T13:31:35+00:00","article_modified_time":"2023-07-18T13:37:02+00:00","og_image":[{"width":1124,"height":613,"url":"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/07\/extraneous-variables-blog.png","type":"image\/png"}],"author":"Jessica Abbadia","twitter_card":"summary_large_image","twitter_title":"Extraneous Variables in Research: Regulating Potential Influences","twitter_description":"Learn about extraneous variables in research and ways for controlling them to increase the internal validity of your research.","twitter_image":"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/07\/extraneous-variables-blog.png","twitter_misc":{"Written by":"Jessica Abbadia","Est. reading time":"5 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/mindthegraph.com\/blog\/es\/variables-extranas\/","url":"https:\/\/mindthegraph.com\/blog\/es\/variables-extranas\/","name":"Extraneous Variables in Research: Regulating Potential Influences - Mind the Graph Blog","isPartOf":{"@id":"https:\/\/mindthegraph.com\/blog\/#website"},"datePublished":"2023-07-18T13:31:35+00:00","dateModified":"2023-07-18T13:37:02+00:00","author":{"@id":"https:\/\/mindthegraph.com\/blog\/#\/schema\/person\/96ecc2d785106e951f7773dc7c96d699"},"description":"Learn about extraneous variables in research and ways for controlling them to increase the internal validity of your research.","breadcrumb":{"@id":"https:\/\/mindthegraph.com\/blog\/es\/variables-extranas\/#breadcrumb"},"inLanguage":"lv","potentialAction":[{"@type":"ReadAction","target":["https:\/\/mindthegraph.com\/blog\/es\/variables-extranas\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/mindthegraph.com\/blog\/es\/variables-extranas\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/mindthegraph.com\/blog\/"},{"@type":"ListItem","position":2,"name":"Extraneous Variables in Research: Regulating Potential Influences"}]},{"@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\/28669"}],"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=28669"}],"version-history":[{"count":4,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/posts\/28669\/revisions"}],"predecessor-version":[{"id":28680,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/posts\/28669\/revisions\/28680"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/media\/28672"}],"wp:attachment":[{"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/media?parent=28669"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/categories?post=28669"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/lv\/wp-json\/wp\/v2\/tags?post=28669"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}