{"id":28012,"date":"2023-05-24T10:07:19","date_gmt":"2023-05-24T13:07:19","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/?p=28012"},"modified":"2023-05-24T10:07:21","modified_gmt":"2023-05-24T13:07:21","slug":"sampling-bias","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/ro\/esantionare-bias\/","title":{"rendered":"O problem\u0103 numit\u0103 prejudecat\u0103 de e\u0219antionare"},"content":{"rendered":"<p>Indiferent de metodologia utilizat\u0103 sau de disciplina studiat\u0103, cercet\u0103torii trebuie s\u0103 se asigure c\u0103 utilizeaz\u0103 e\u0219antioane reprezentative care reflect\u0103 caracteristicile popula\u021biei pe care o studiaz\u0103. Acest articol va explora conceptul de p\u0103rtinire a e\u0219antion\u0103rii, diferitele sale tipuri \u0219i modalit\u0103\u021bi de aplicare, precum \u0219i cele mai bune practici pentru a atenua efectele sale.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Ce este prejudecata de e\u0219antionare?<\/h2>\n\n\n\n<p>Prejudiciul de e\u0219antionare se refer\u0103 la o situa\u021bie \u00een care anumite persoane sau grupuri dintr-o popula\u021bie au o probabilitate mai mare de a fi incluse \u00eentr-un e\u0219antion dec\u00e2t altele, ceea ce duce la un e\u0219antion p\u0103rtinitor sau nereprezentativ. Acest lucru se poate \u00eent\u00e2mpla dintr-o varietate de motive, cum ar fi metodele de e\u0219antionare nealeatoare, prejudecata de auto-selec\u021bie sau prejudecata cercet\u0103torului.<\/p>\n\n\n\n<p>Cu alte cuvinte, prejudecata de e\u0219antionare poate submina validitatea \u0219i generalizabilitatea rezultatelor cercet\u0103rii prin distorsionarea e\u0219antionului \u00een favoarea anumitor caracteristici sau perspective care ar putea s\u0103 nu fie reprezentative pentru popula\u021bia mai mare.&nbsp;<\/p>\n\n\n\n<p>\u00cen mod ideal, trebuie s\u0103 selecta\u021bi to\u021bi participan\u021bii la sondaj \u00een mod aleatoriu. Cu toate acestea, \u00een practic\u0103, poate fi dificil s\u0103 se fac\u0103 o selec\u021bie aleatorie a participan\u021bilor din cauza unor constr\u00e2ngeri precum costurile \u0219i disponibilitatea responden\u021bilor. Chiar dac\u0103 nu face\u021bi o colectare aleatorie a datelor, este esen\u021bial s\u0103 fi\u021bi con\u0219tient de poten\u021bialele prejudec\u0103\u021bi care ar putea fi prezente \u00een datele dumneavoastr\u0103.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">C\u00e2teva exemple de prejudec\u0103\u021bi de e\u0219antionare includ:<\/h3>\n\n\n\n<ol>\n<li><strong>Prejudiciu de voluntariat<\/strong>: Participan\u021bii care se ofer\u0103 voluntar s\u0103 participe la un studiu ar putea avea caracteristici diferite fa\u021b\u0103 de cei care nu se ofer\u0103 voluntar, ceea ce ar putea duce la un e\u0219antion nereprezentativ.<\/li>\n\n\n\n<li><strong>E\u0219antionare nealeatorie<\/strong>: \u00cen cazul \u00een care un cercet\u0103tor selecteaz\u0103 participan\u021bii numai din anumite loca\u021bii sau selecteaz\u0103 numai participan\u021bi cu anumite caracteristici, se poate ajunge la un e\u0219antion tenden\u021bios.<\/li>\n\n\n\n<li><strong>Prejudiciul de supravie\u021buire<\/strong>: Acest lucru se \u00eent\u00e2mpl\u0103 atunci c\u00e2nd un e\u0219antion include doar persoane care au supravie\u021buit sau au reu\u0219it \u00eentr-o anumit\u0103 situa\u021bie, l\u0103s\u00e2ndu-i \u00een afara celor care nu au supravie\u021buit sau au e\u0219uat.<\/li>\n\n\n\n<li><strong>E\u0219antionare de convenien\u021b\u0103<\/strong>: Acest tip de e\u0219antionare implic\u0103 selectarea participan\u021bilor care sunt u\u0219or de accesat, cum ar fi cei care se \u00eent\u00e2mpl\u0103 s\u0103 fie \u00een apropiere sau cei care r\u0103spund la un sondaj online, care ar putea s\u0103 nu reprezinte popula\u021bia mai mare.<\/li>\n\n\n\n<li><strong>Prejudecata de confirmare<\/strong>: Cercet\u0103torii ar putea selecta - \u00een mod incon\u0219tient sau deliberat - participan\u021bi care s\u0103 le sus\u021bin\u0103 ipoteza sau \u00eentrebarea de cercetare, ceea ce duce la rezultate p\u0103rtinitoare.<\/li>\n\n\n\n<li><strong>Efectul Hawthorne<\/strong>: Participan\u021bii \u00ee\u0219i pot modifica comportamentul sau r\u0103spunsurile atunci c\u00e2nd \u0219tiu c\u0103 sunt studia\u021bi sau observa\u021bi, ceea ce poate duce la rezultate nereprezentative.<\/li>\n<\/ol>\n\n\n\n<p>&nbsp;Dac\u0103 sunte\u021bi con\u0219tien\u021bi de aceste prejudec\u0103\u021bi, le pute\u021bi lua \u00een considerare \u00een analiz\u0103 pentru a corecta prejudec\u0103\u021bile \u0219i pentru a \u00een\u021belege mai bine popula\u021bia pe care o reprezint\u0103 datele dumneavoastr\u0103.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Tipuri de prejudec\u0103\u021bi de e\u0219antionare<\/h2>\n\n\n\n<ul>\n<li><strong>Bias de selec\u021bie<\/strong>: apare atunci c\u00e2nd e\u0219antionul nu este reprezentativ pentru popula\u021bie.<\/li>\n\n\n\n<li><strong>Prejudiciu de m\u0103surare<\/strong>: apare atunci c\u00e2nd datele colectate sunt inexacte sau incomplete.<\/li>\n\n\n\n<li><strong>Prejudiciul de raportare<\/strong>: apare atunci c\u00e2nd responden\u021bii furnizeaz\u0103 informa\u021bii inexacte sau incomplete.<\/li>\n\n\n\n<li><strong>Biasarea non-r\u0103spunsului<\/strong>: apare atunci c\u00e2nd unii membri ai popula\u021biei nu r\u0103spund la sondaj, ceea ce duce la un e\u0219antion nereprezentativ.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Cauzele prejudec\u0103\u021bilor de e\u0219antionare<\/h2>\n\n\n\n<ol>\n<li><strong>E\u0219antionare de convenien\u021b\u0103<\/strong>: selectarea unui e\u0219antion bazat pe comoditate, mai degrab\u0103 dec\u00e2t pe utilizarea unei metode \u0219tiin\u021bifice.<\/li>\n\n\n\n<li><strong>Bias de auto-selec\u021bie<\/strong>: sunt inclu\u0219i doar cei care se ofer\u0103 voluntar s\u0103 participe la sondaj, ceea ce poate s\u0103 nu fie reprezentativ pentru popula\u021bie.<\/li>\n\n\n\n<li><strong>Prejudiciul cadrului de e\u0219antionare<\/strong>: atunci c\u00e2nd cadrul de e\u0219antionare utilizat pentru a selecta e\u0219antionul nu este reprezentativ pentru popula\u021bie.<\/li>\n\n\n\n<li><strong>\u00cenclina\u021bia de supravie\u021buire<\/strong>: atunci c\u00e2nd doar anumi\u021bi membri ai popula\u021biei particip\u0103, ceea ce duce la un e\u0219antion nereprezentativ. De exemplu, dac\u0103 cercet\u0103torii intervieveaz\u0103 doar persoanele care sunt \u00een via\u021b\u0103, este posibil s\u0103 nu primeasc\u0103 informa\u021bii de la persoanele care au murit \u00eenainte de efectuarea studiului.<\/li>\n\n\n\n<li><strong>Prejudiciu de e\u0219antionare datorat lipsei de cuno\u0219tin\u021be<\/strong>: nerecunoa\u0219terea surselor de variabilitate care pot duce la estim\u0103ri distorsionate.<\/li>\n\n\n\n<li><strong>Prejudiciu de e\u0219antionare datorat erorilor \u00een administrarea e\u0219antionului<\/strong>: neutilizarea unui cadru de e\u0219antionare adecvat sau care func\u021bioneaz\u0103 bine sau refuzul de a participa la studiu, ceea ce duce la o selec\u021bie p\u0103rtinitoare a e\u0219antionului.<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Biasul de e\u0219antionare \u00een studiile clinice<\/h2>\n\n\n\n<p>Studiile clinice au rolul de a testa eficacitatea unui nou tratament sau medicament pe o anumit\u0103 popula\u021bie. Acestea reprezint\u0103 o parte esen\u021bial\u0103 a procesului de dezvoltare a medicamentelor \u0219i determin\u0103 dac\u0103 un tratament este sigur \u0219i eficient \u00eenainte de a fi lansat pentru publicul larg. Cu toate acestea, studiile clinice sunt, de asemenea, predispuse la prejudec\u0103\u021bi de selec\u021bie.<\/p>\n\n\n\n<p>Biasul de selec\u021bie apare atunci c\u00e2nd e\u0219antionul utilizat pentru un studiu nu este reprezentativ pentru popula\u021bia pe care trebuie s\u0103 o reprezinte. \u00cen cazul studiilor clinice, tendin\u021ba de selec\u021bie poate ap\u0103rea atunci c\u00e2nd participan\u021bii sunt fie ale\u0219i \u00een mod selectiv pentru a participa, fie sunt auto-selecta\u021bi.<\/p>\n\n\n\n<p>S\u0103 spunem c\u0103 o companie farmaceutic\u0103 desf\u0103\u0219oar\u0103 un studiu clinic pentru a testa eficacitatea unui nou medicament \u00eempotriva cancerului. Aceasta decide s\u0103 recruteze participan\u021bi pentru studiu prin anun\u021buri \u00een spitale, clinici \u0219i grupuri de sprijin pentru bolnavii de cancer, precum \u0219i prin aplica\u021bii online. Cu toate acestea, este posibil ca e\u0219antionul pe care \u00eel colecteaz\u0103 s\u0103 fie \u00eenclinat c\u0103tre cei care sunt mai motiva\u021bi s\u0103 participe la un studiu sau care au un anumit tip de cancer. Acest lucru poate face dificil\u0103 generalizarea rezultatelor studiului la o popula\u021bie mai mare.<\/p>\n\n\n\n<p>Pentru a minimiza prejudec\u0103\u021bile de selec\u021bie \u00een studiile clinice, cercet\u0103torii trebuie s\u0103 implementeze criterii stricte de includere \u0219i excludere \u0219i procese de selec\u021bie aleatorie. Acest lucru va asigura faptul c\u0103 e\u0219antionul de participan\u021bi selectat pentru studiu este reprezentativ pentru popula\u021bia mai mare, minimiz\u00e2nd orice prejudecat\u0103 \u00een datele colectate.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Probleme datorate prejudec\u0103\u021bilor de e\u0219antionare<\/h2>\n\n\n\n<p>Prejudiciul de e\u0219antionare este problematic deoarece este posibil ca o statistic\u0103 calculat\u0103 pe e\u0219antion s\u0103 fie sistematic eronat\u0103. Aceasta poate duce la o supraestimare sau subestimare sistematic\u0103 a parametrului corespunz\u0103tor \u00een popula\u021bie. Acest fenomen apare \u00een practic\u0103, deoarece este practic imposibil s\u0103 se asigure o aleatorizare perfect\u0103 \u00een e\u0219antionare.<\/p>\n\n\n\n<p>\u00cen cazul \u00een care gradul de denaturare este mic, atunci e\u0219antionul poate fi tratat ca o aproximare rezonabil\u0103 a unui e\u0219antion aleatoriu. \u00cen plus, \u00een cazul \u00een care e\u0219antionul nu difer\u0103 \u00een mod semnificativ \u00een ceea ce prive\u0219te cantitatea m\u0103surat\u0103, atunci un e\u0219antion distorsionat poate fi \u00een continuare o estimare rezonabil\u0103.<\/p>\n\n\n\n<p>\u00cen timp ce unele persoane ar putea folosi \u00een mod deliberat un e\u0219antion tenden\u021bios pentru a produce rezultate \u00een\u0219el\u0103toare, cel mai adesea, un e\u0219antion tenden\u021bios este doar o reflectare a dificult\u0103\u021bii de a ob\u021bine un e\u0219antion cu adev\u0103rat reprezentativ sau a ignor\u0103rii tenden\u021biozit\u0103\u021bii \u00een procesul lor de m\u0103surare sau analiz\u0103.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Extrapolare: dincolo de interval<\/h2>\n\n\n\n<p>\u00cen statistic\u0103, extragerea unei concluzii despre ceva care dep\u0103\u0219e\u0219te limitele datelor se nume\u0219te extrapolare. Tragerea unei concluzii dintr-un e\u0219antion tenden\u021bios este o form\u0103 de extrapolare: deoarece metoda de e\u0219antionare exclude \u00een mod sistematic anumite p\u0103r\u021bi din popula\u021bia luat\u0103 \u00een considerare, concluziile se aplic\u0103 doar subpopula\u021biei e\u0219antionate.<\/p>\n\n\n\n<p>Extrapolarea are loc, de asemenea, dac\u0103, de exemplu, o inferen\u021b\u0103 bazat\u0103 pe un e\u0219antion de studen\u021bi universitari este aplicat\u0103 adul\u021bilor mai \u00een v\u00e2rst\u0103 sau adul\u021bilor cu o educa\u021bie de doar clasa a opta. Extrapolarea este o eroare frecvent\u0103 \u00een aplicarea sau interpretarea statisticilor. Uneori, din cauza dificult\u0103\u021bii sau a imposibilit\u0103\u021bii de a ob\u021bine date bune, extrapolarea este tot ce putem face mai bine, dar \u00eentotdeauna trebuie luat\u0103 cu cel pu\u021bin un gr\u0103unte de sare - \u0219i adesea cu o doz\u0103 mare de incertitudine<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">De la \u0219tiin\u021b\u0103 la pseudo\u0219tiin\u021b\u0103<\/h2>\n\n\n\n<p><a href=\"https:\/\/en.wikipedia.org\/wiki\/Sampling_bias\">Dup\u0103 cum se men\u021bioneaz\u0103 pe Wikipedia<\/a>, un exemplu al modului \u00een care poate exista ignorarea unei prejudec\u0103\u021bi este utilizarea pe scar\u0103 larg\u0103 a unui raport (cunoscut \u0219i sub numele de \"fold change\") ca o m\u0103sur\u0103 a diferen\u021bei \u00een biologie. Deoarece este mai u\u0219or s\u0103 se ob\u021bin\u0103 un raport mare cu dou\u0103 numere mici cu o anumit\u0103 diferen\u021b\u0103 \u0219i relativ mai dificil s\u0103 se ob\u021bin\u0103 un raport mare cu dou\u0103 numere mari cu o diferen\u021b\u0103 mai mare, diferen\u021bele semnificative mari pot fi omise atunci c\u00e2nd se compar\u0103 m\u0103sur\u0103tori numerice relativ mari.&nbsp;<\/p>\n\n\n\n<p>Unii au numit acest lucru \"prejudecat\u0103 de demarca\u021bie\", deoarece utilizarea unui raport (\u00eemp\u0103r\u021bire) \u00een loc de o diferen\u021b\u0103 (sc\u0103dere) transform\u0103 rezultatele analizei din \u0219tiin\u021b\u0103 \u00een pseudo\u0219tiin\u021b\u0103.<\/p>\n\n\n\n<p>Unele e\u0219antioane utilizeaz\u0103 un plan statistic distorsionat, care permite totu\u0219i estimarea parametrilor. De exemplu, Centrul Na\u021bional de Statistic\u0103 \u00een domeniul S\u0103n\u0103t\u0103\u021bii din SUA suprae\u0219antioneaz\u0103 \u00een mod deliberat popula\u021biile minoritare \u00een multe dintre anchetele sale la nivel na\u021bional, pentru a ob\u021bine o precizie suficient\u0103 pentru estim\u0103rile \u00een cadrul acestor grupuri.<\/p>\n\n\n\n<p>Aceste anchete necesit\u0103 utilizarea unor ponder\u0103ri ale e\u0219antionului pentru a produce estim\u0103ri adecvate pentru toate grupurile etnice. \u00cen cazul \u00een care sunt \u00eendeplinite anumite condi\u021bii (\u00een principal, dac\u0103 ponderile sunt calculate \u0219i utilizate corect), aceste e\u0219antioane permit o estimare precis\u0103 a parametrilor popula\u021biei.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Cele mai bune practici pentru atenuarea prejudec\u0103\u021bilor de e\u0219antionare<\/h2>\n\n\n\n<p>Este esen\u021bial s\u0103 se selecteze o metod\u0103 de e\u0219antionare adecvat\u0103 pentru a se asigura c\u0103 datele rezultate reflect\u0103 cu exactitate popula\u021bia studiat\u0103.<\/p>\n\n\n\n<ol>\n<li><strong>Tehnici de e\u0219antionare aleatorie<\/strong>: Utilizarea tehnicilor de e\u0219antionare aleatorie cre\u0219te probabilitatea ca e\u0219antionul s\u0103 fie reprezentativ pentru popula\u021bie. Aceast\u0103 tehnic\u0103 ajut\u0103 la asigurarea faptului c\u0103 e\u0219antionul este c\u00e2t mai reprezentativ posibil pentru popula\u021bia \u00een cauz\u0103 \u0219i, astfel, este mai pu\u021bin probabil s\u0103 con\u021bin\u0103 prejudec\u0103\u021bi.<\/li>\n\n\n\n<li><strong>Calcularea m\u0103rimii e\u0219antionului<\/strong>: Calcularea dimensiunii e\u0219antionului trebuie s\u0103 se fac\u0103 astfel \u00eenc\u00e2t s\u0103 existe o putere adecvat\u0103 pentru a testa ipoteze semnificative din punct de vedere statistic. Cu c\u00e2t dimensiunea e\u0219antionului este mai mare, cu at\u00e2t este mai bine reprezentat\u0103 popula\u021bia.<\/li>\n\n\n\n<li><strong>Analiza tendin\u021belor<\/strong>: C\u0103utarea unor surse de date alternative \u0219i analiza oric\u0103ror tendin\u021be observate \u00een datele care pot fi neselectate.<\/li>\n\n\n\n<li><strong>Verificarea prejudec\u0103\u021bilor<\/strong>: Ar trebui monitorizate apari\u021biile de p\u0103rtinire pentru a identifica excluderea sau supraincluderea sistematic\u0103 a unor puncte de date specifice.<\/li>\n<\/ol>\n\n\n\n<p><strong>Aten\u021bie la e\u0219antioane<\/strong><\/p>\n\n\n\n<p>Prejudiciul de e\u0219antionare este un aspect important atunci c\u00e2nd se efectueaz\u0103 cercet\u0103ri. Indiferent de metodologia utilizat\u0103 sau de disciplina studiat\u0103, cercet\u0103torii trebuie s\u0103 se asigure c\u0103 utilizeaz\u0103 e\u0219antioane reprezentative care reflect\u0103 caracteristicile popula\u021biei pe care o studiaz\u0103.<\/p>\n\n\n\n<p>Atunci c\u00e2nd se creeaz\u0103 studii de cercetare, este esen\u021bial s\u0103 se acorde o aten\u021bie deosebit\u0103 procesului de selec\u021bie a e\u0219antionului, precum \u0219i metodologiei utilizate pentru a colecta date din e\u0219antion. Ar trebui utilizate cele mai bune practici, cum ar fi tehnicile de e\u0219antionare aleatorie, calcularea dimensiunii e\u0219antionului, analiza tendin\u021belor \u0219i verificarea tendin\u021belor de p\u0103rtinire, pentru a se asigura c\u0103 rezultatele cercet\u0103rii sunt valide \u0219i fiabile, ceea ce le face mai susceptibile de a influen\u021ba politicile \u0219i practicile.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Infografice \u0219tiin\u021bifice atr\u0103g\u0103toare \u00een c\u00e2teva minute<\/h2>\n\n\n\n<p><a href=\"http:\/\/mindthegraph.com\/\">Mind the Graph<\/a> este un instrument online puternic pentru oamenii de \u0219tiin\u021b\u0103 care au nevoie s\u0103 creeze grafice \u0219i ilustra\u021bii \u0219tiin\u021bifice de \u00eenalt\u0103 calitate. Platforma este u\u0219or de utilizat \u0219i este accesibil\u0103 oamenilor de \u0219tiin\u021b\u0103 cu diferite niveluri de expertiz\u0103 tehnic\u0103, ceea ce o face o solu\u021bie ideal\u0103 pentru cercet\u0103torii care trebuie s\u0103 creeze grafic\u0103 pentru publica\u021biile, prezent\u0103rile \u0219i alte materiale de comunicare \u0219tiin\u021bific\u0103.<\/p>\n\n\n\n<p>Indiferent dac\u0103 sunte\u021bi cercet\u0103tor \u00een domeniul \u0219tiin\u021belor vie\u021bii, al \u0219tiin\u021belor fizice sau al ingineriei, Mind the Graph ofer\u0103 o gam\u0103 larg\u0103 de resurse pentru a v\u0103 ajuta s\u0103 v\u0103 comunica\u021bi rezultatele cercet\u0103rii \u00eentr-un mod clar \u0219i conving\u0103tor din punct de vedere vizual.<\/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=\"338\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2022\/10\/r3qiu0qenda-3.gif\" alt=\"\" class=\"wp-image-25130\"\/><\/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\/app\/offer-trial\" style=\"border-radius:50px;background-color:#dc1866\" target=\"_blank\" rel=\"noreferrer noopener\">\u00cencepe\u021bi s\u0103 crea\u021bi infografice gratuit<\/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>Prejudiciul de e\u0219antionare este un aspect critic atunci c\u00e2nd se efectueaz\u0103 cercet\u0103ri \u00een cadrul unor discipline precum statistica, \u0219tiin\u021bele sociale \u0219i epidemiologia. <\/p>","protected":false},"author":38,"featured_media":28013,"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>A problem called Sampling bias - Mind the Graph Blog<\/title>\n<meta name=\"description\" content=\"Sampling bias is a critical consideration when conducting research within disciplines such as statistics, social science, and epidemiology.\" \/>\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\/ro\/esantionare-bias\/\" \/>\n<meta property=\"og:locale\" content=\"ro_RO\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"A problem called Sampling bias\" \/>\n<meta property=\"og:description\" content=\"Sampling bias is a critical consideration when conducting research within disciplines such as statistics, social science, and epidemiology.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/mindthegraph.com\/blog\/ro\/esantionare-bias\/\" \/>\n<meta property=\"og:site_name\" content=\"Mind the Graph Blog\" \/>\n<meta property=\"article:published_time\" content=\"2023-05-24T13:07:19+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2023-05-24T13:07:21+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/05\/sampling-bias-blog.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1123\" \/>\n\t<meta property=\"og:image:height\" content=\"612\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Gilberto de Abreu\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:title\" content=\"A problem called Sampling bias\" \/>\n<meta name=\"twitter:description\" content=\"Sampling bias is a critical consideration when conducting research within disciplines such as statistics, social science, and epidemiology.\" \/>\n<meta name=\"twitter:image\" content=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/05\/sampling-bias-blog.jpg\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Gilberto de Abreu\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"8 minutes\" \/>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"A problem called Sampling bias - Mind the Graph Blog","description":"Sampling bias is a critical consideration when conducting research within disciplines such as statistics, social science, and epidemiology.","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\/ro\/esantionare-bias\/","og_locale":"ro_RO","og_type":"article","og_title":"A problem called Sampling bias","og_description":"Sampling bias is a critical consideration when conducting research within disciplines such as statistics, social science, and epidemiology.","og_url":"https:\/\/mindthegraph.com\/blog\/ro\/esantionare-bias\/","og_site_name":"Mind the Graph Blog","article_published_time":"2023-05-24T13:07:19+00:00","article_modified_time":"2023-05-24T13:07:21+00:00","og_image":[{"width":1123,"height":612,"url":"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/05\/sampling-bias-blog.jpg","type":"image\/jpeg"}],"author":"Gilberto de Abreu","twitter_card":"summary_large_image","twitter_title":"A problem called Sampling bias","twitter_description":"Sampling bias is a critical consideration when conducting research within disciplines such as statistics, social science, and epidemiology.","twitter_image":"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/05\/sampling-bias-blog.jpg","twitter_misc":{"Written by":"Gilberto de Abreu","Est. reading time":"8 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/mindthegraph.com\/blog\/sampling-bias\/","url":"https:\/\/mindthegraph.com\/blog\/sampling-bias\/","name":"A problem called Sampling bias - Mind the Graph Blog","isPartOf":{"@id":"https:\/\/mindthegraph.com\/blog\/#website"},"datePublished":"2023-05-24T13:07:19+00:00","dateModified":"2023-05-24T13:07:21+00:00","author":{"@id":"https:\/\/mindthegraph.com\/blog\/#\/schema\/person\/b28781b05825270dad9cba59503a9321"},"description":"Sampling bias is a critical consideration when conducting research within disciplines such as statistics, social science, and epidemiology.","breadcrumb":{"@id":"https:\/\/mindthegraph.com\/blog\/sampling-bias\/#breadcrumb"},"inLanguage":"ro-RO","potentialAction":[{"@type":"ReadAction","target":["https:\/\/mindthegraph.com\/blog\/sampling-bias\/"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/mindthegraph.com\/blog\/sampling-bias\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/mindthegraph.com\/blog\/"},{"@type":"ListItem","position":2,"name":"A problem called Sampling bias"}]},{"@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":"ro-RO"},{"@type":"Person","@id":"https:\/\/mindthegraph.com\/blog\/#\/schema\/person\/b28781b05825270dad9cba59503a9321","name":"Gilberto de Abreu","image":{"@type":"ImageObject","inLanguage":"ro-RO","@id":"https:\/\/mindthegraph.com\/blog\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/cc861028818e8a4fffa388f920fbdae9?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/cc861028818e8a4fffa388f920fbdae9?s=96&d=mm&r=g","caption":"Gilberto de Abreu"},"url":"https:\/\/mindthegraph.com\/blog\/ro\/author\/giba\/"}]}},"_links":{"self":[{"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/posts\/28012"}],"collection":[{"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/users\/38"}],"replies":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/comments?post=28012"}],"version-history":[{"count":3,"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/posts\/28012\/revisions"}],"predecessor-version":[{"id":28023,"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/posts\/28012\/revisions\/28023"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/media\/28013"}],"wp:attachment":[{"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/media?parent=28012"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/categories?post=28012"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mindthegraph.com\/blog\/ro\/wp-json\/wp\/v2\/tags?post=28012"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}