{"id":29892,"date":"2023-10-14T06:04:00","date_gmt":"2023-10-14T09:04:00","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/academic-report-format-copy\/"},"modified":"2023-10-10T18:12:07","modified_gmt":"2023-10-10T21:12:07","slug":"ordinal-data-examples","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/tr\/sirali-veri-ornekleri\/","title":{"rendered":"S\u0131ral\u0131 Verileri Ke\u015ffetmek: \u00d6rnekler ve Kullan\u0131mlar"},"content":{"rendered":"

Ara\u015ft\u0131rma ve veri analizi alan\u0131nda, farkl\u0131 veri t\u00fcrlerini anlamak, anlaml\u0131 sonu\u00e7lar \u00e7\u0131karmak ve bilin\u00e7li kararlar almak i\u00e7in \u00e7ok \u00f6nemlidir. Bu t\u00fcrlerden biri de sosyal bilimlerden pazar ara\u015ft\u0131rmalar\u0131na kadar \u00e7e\u015fitli disiplinlerde \u00f6nemli bir rol oynayan s\u0131ral\u0131 verilerdir. S\u0131ral\u0131 verilerin neyi temsil etti\u011fini ve di\u011fer veri t\u00fcrlerinden nas\u0131l farkl\u0131la\u015ft\u0131\u011f\u0131n\u0131 anlamak, veri k\u00fcmelerinden anlaml\u0131 i\u00e7g\u00f6r\u00fcler elde etmeyi ama\u00e7layan ara\u015ft\u0131rmac\u0131lar i\u00e7in \u00e7ok \u00f6nemlidir. Bu makale, s\u0131ral\u0131 verinin ne oldu\u011fu ve ara\u015ft\u0131rma alan\u0131ndaki \u00f6nemi hakk\u0131nda kapsaml\u0131 bir a\u00e7\u0131klama sa\u011flayacakt\u0131r.<\/p>\n\n\n\n

S\u0131ral\u0131 Veri Nedir?<\/strong><\/h2>\n\n\n\n

S\u0131ral\u0131 veri, kategorilerin do\u011fal bir d\u00fczene veya s\u0131ralamaya sahip oldu\u011fu bir kategorik veri t\u00fcr\u00fcd\u00fcr. Bu, kategorilerin g\u00f6receli de\u011ferlerine veya \u00f6nemlerine g\u00f6re s\u0131ralanabilecekleri veya s\u0131ralanabilecekleri \u015fekilde s\u0131raland\u0131klar\u0131 anlam\u0131na gelir. \u00d6rne\u011fin, kat\u0131l\u0131mc\u0131lardan kat\u0131lma d\u00fczeylerini 1 ila 5 aras\u0131nda derecelendirmelerini isteyen bir anket sorusu, yan\u0131tlar \"kesinlikle kat\u0131lm\u0131yorum\" (1) ile \"kesinlikle kat\u0131l\u0131yorum\" (5) aras\u0131nda do\u011fal bir s\u0131raya sahip oldu\u011fundan ordinal veri toplamaktad\u0131r. Ordinal veri \u00f6rnekleri ki-kare testleri gibi istatistiksel y\u00f6ntemler kullan\u0131larak analiz edilebilir, ancak kategoriler aras\u0131ndaki mesafeler e\u015fit olmayabilece\u011finden biraz dikkatli olunmas\u0131 gerekir.<\/p>\n\n\n\n

S\u0131ral\u0131 veriler bilimsel ara\u015ft\u0131rmalarda \u00e7ok \u00f6nemlidir, \u00e7\u00fcnk\u00fc verilerin do\u011fal bir d\u00fczen veya s\u0131ralama ile s\u0131n\u0131fland\u0131r\u0131lmas\u0131n\u0131 ve kar\u015f\u0131la\u015ft\u0131r\u0131lmas\u0131n\u0131 sa\u011flar, bu da verilerdeki kal\u0131plar, ili\u015fkiler ve e\u011filimler hakk\u0131nda de\u011ferli bilgiler sa\u011flayabilir. Bu t\u00fcr veriler, kat\u0131l\u0131mc\u0131lardan g\u00f6r\u00fc\u015flerini veya deneyimlerini bir \u00f6l\u00e7ek \u00fczerinde derecelendirmelerinin istendi\u011fi anketler ve soru formlar\u0131 gibi sosyal bilim ara\u015ft\u0131rmalar\u0131nda s\u0131kl\u0131kla kullan\u0131l\u0131r.<\/p>\n\n\n\n

\u015eekil: https:\/\/www.voxco.com\/wp-content\/uploads\/2021\/03\/Cover-scale-1536\u00d7864.jpg<\/p>\n\n\n\n

Ordinal Verilerin \u00d6zellikleri<\/strong><\/h2>\n\n\n\n

S\u0131ral\u0131 veriler, kategorileri aras\u0131nda belirli bir s\u0131ra veya s\u0131ralamay\u0131 temsil eden bir kategorik veri t\u00fcr\u00fcd\u00fcr. A\u015fa\u011f\u0131da s\u0131ral\u0131 verilerin baz\u0131 temel \u00f6zellikleri verilmi\u015ftir:<\/p>\n\n\n\n

Sipari\u015f verin: <\/strong>S\u0131ral\u0131 verilerdeki kategorilerin belirli bir d\u00fczeni veya s\u0131ralamas\u0131 vard\u0131r ve bu d\u00fczen kat\u0131lma, kat\u0131lmama veya tercih d\u00fczeyini temsil eder. \u00d6rne\u011fin, al\u0131nan hizmetin kalitesinin soruldu\u011fu bir ankette yan\u0131t se\u00e7enekleri \"m\u00fckemmel\", \"iyi\", \"orta\" veya \"zay\u0131f\" olabilir ve bunlar net bir s\u0131ralamaya sahip olacakt\u0131r.<\/p>\n\n\n\n

Say\u0131sal olmayan:<\/strong> <\/em>S\u0131ral\u0131 veri kategorilerinin say\u0131larla temsil edilmesi zorunlu de\u011fildir ve kategoriler kelimeler veya semboller olabilir. \u00d6rne\u011fin, bir restoran derecelendirme sistemi kalite seviyelerini belirtmek i\u00e7in say\u0131sal de\u011ferler yerine y\u0131ld\u0131zlar kullanabilir.<\/p>\n\n\n\n

E\u015fit olmayan aral\u0131klar:<\/strong> <\/em>Kategoriler aras\u0131ndaki mesafelerin e\u015fit olmas\u0131 gerekmez. \u00d6rne\u011fin, bir Likert \u00f6l\u00e7e\u011finde \"kesinlikle kat\u0131l\u0131yorum\" ile \"kat\u0131l\u0131yorum\" aras\u0131ndaki fark, \"kat\u0131lm\u0131yorum\" ile \"kesinlikle kat\u0131lm\u0131yorum\" aras\u0131ndaki farkla ayn\u0131 olmayabilir.<\/p>\n\n\n\n

S\u0131n\u0131rl\u0131 say\u0131da kategori:<\/strong> S\u0131ral\u0131 veriler tipik olarak s\u0131n\u0131rl\u0131 say\u0131da kategoriye sahiptir ve bu kategoriler genellikle ara\u015ft\u0131rmac\u0131 taraf\u0131ndan \u00f6nceden tan\u0131mlan\u0131r. \u00d6rne\u011fin, bir anket be\u015f yan\u0131t se\u00e7ene\u011fi olan bir Likert \u00f6l\u00e7e\u011fi kullanabilir.<\/p>\n\n\n\n

Say\u0131sal veri olarak ele al\u0131nabilir: <\/strong>Bazen s\u0131ral\u0131 veriler istatistiksel analiz amac\u0131yla say\u0131sal veriler olarak ele al\u0131nabilir, ancak bu dikkatli bir \u015fekilde yap\u0131lmal\u0131d\u0131r. S\u0131ral\u0131 kategorilere anlaml\u0131 say\u0131sal de\u011ferler atamak analiz ve yorumlamay\u0131 kolayla\u015ft\u0131rabilir, ancak verilerin temel niteli\u011fini de\u011fi\u015ftirmemelidir.<\/p>\n\n\n\n

Ordinal De\u011fi\u015fken T\u00fcrleri<\/strong><\/h2>\n\n\n\n

S\u0131ral\u0131 de\u011fi\u015fkenler, de\u011ferlerine veya niteliklerine g\u00f6re s\u0131ralanabilen veya s\u0131ralanabilen de\u011fi\u015fkenlerdir. \u0130ki t\u00fcr s\u0131ral\u0131 de\u011fi\u015fken vard\u0131r:<\/p>\n\n\n\n

E\u015fle\u015fen Kategori<\/h3>\n\n\n\n

E\u015fle\u015ftirilmi\u015f kategori s\u0131ral\u0131 de\u011fi\u015fkenlerde, de\u011fi\u015fkenin kategorilerinde do\u011fal bir d\u00fczen vard\u0131r. Bu s\u0131ralama de\u011fi\u015fkenin kendisi taraf\u0131ndan tan\u0131mlan\u0131r ve kategoriler birbirini d\u0131\u015flar. \u00d6rne\u011fin, bir \u00f6nce ve sonra \u00e7al\u0131\u015fma tasar\u0131m\u0131nda, ayn\u0131 kat\u0131l\u0131mc\u0131 grubu, bir tedaviden \u00f6nce ve sonra gibi iki farkl\u0131 noktada ayn\u0131 s\u0131ral\u0131 de\u011fi\u015fken \u00fczerinde \u00f6l\u00e7\u00fcl\u00fcr. \"\u00d6nce\" \u00f6l\u00e7\u00fcm\u00fcndeki kategoriler \"sonra\" \u00f6l\u00e7\u00fcm\u00fcndeki kategorilerle e\u015fle\u015ftirilir veya e\u015fle\u015ftirilir. <\/p>\n\n\n\n

Bir ba\u015fka \u00f6rnek de, \u00e7iftlerin tercihlerini belirli bir a\u00e7\u0131dan kar\u015f\u0131la\u015ft\u0131ran ve bir e\u015fin tercihlerinin di\u011fer e\u015fin tercihleriyle e\u015fle\u015ftirildi\u011fi veya e\u015fle\u015ftirildi\u011fi bir \u00e7al\u0131\u015fmad\u0131r. E\u015fle\u015ftirilmi\u015f kategoriler, her bir \u00e7ift veya grup i\u00e7indeki kategoriler aras\u0131ndaki farklar\u0131 kar\u015f\u0131la\u015ft\u0131rmak i\u00e7in genellikle Wilcoxon signed-rank testi veya Friedman testi gibi parametrik olmayan istatistiksel testler kullan\u0131larak analiz edilir.<\/p>\n\n\n\n

E\u015fsiz Kategori<\/h3>\n\n\n\n

E\u015fle\u015fmeyen kategori bir ba\u015fka s\u0131ral\u0131 de\u011fi\u015fken t\u00fcr\u00fcd\u00fcr. E\u015fle\u015fen kategorilerin aksine, e\u015fle\u015fmeyen kategoriler aras\u0131nda net bir ili\u015fki veya ba\u011flant\u0131 yoktur. \u00d6rne\u011fin, kat\u0131l\u0131mc\u0131lardan farkl\u0131 m\u00fczik t\u00fcrlerine y\u00f6nelik tercihlerini derecelendirmelerini istiyorsan\u0131z, caz, country ve rock kategorileri aras\u0131nda net bir s\u0131ralama veya ili\u015fki olmayabilir.<\/p>\n\n\n\n

E\u015fle\u015fmeyen kategorilerde, kategoriler yine de bir kat\u0131l\u0131mc\u0131n\u0131n bireysel tercihlerine veya alg\u0131lar\u0131na g\u00f6re s\u0131ralanabilir, ancak t\u00fcm kat\u0131l\u0131mc\u0131lar i\u00e7in ge\u00e7erli olan nesnel veya tutarl\u0131 bir s\u0131ralama yoktur. Bu durum, net ve tutarl\u0131 bir s\u0131ralamaya sahip olan e\u015fle\u015ftirilmi\u015f kategorilere k\u0131yasla verilerin analiz edilmesini ve yorumlanmas\u0131n\u0131 daha zor hale getirebilir.<\/p>\n\n\n\n

S\u0131ral\u0131 Veri \u00d6rnekleri<\/strong><\/h2>\n\n\n\n

S\u0131ral\u0131 veri \u00f6rnekleri bir\u00e7ok ara\u015ft\u0131rma alan\u0131nda ve \u00e7e\u015fitli \u00f6l\u00e7\u00fcm t\u00fcrlerinde bulunabilir. S\u0131ral\u0131 verilere baz\u0131 \u00f6rnekler \u015funlard\u0131r:<\/p>\n\n\n\n

Aral\u0131k \u00d6l\u00e7e\u011fi<\/h3>\n\n\n\n

Aral\u0131k \u00f6l\u00e7e\u011fi, her kategoriye veya yan\u0131ta say\u0131sal bir de\u011fer atanan ve de\u011ferler aras\u0131ndaki farklar\u0131n anlaml\u0131 ve e\u015fit oldu\u011fu bir \u00f6l\u00e7\u00fcm \u00f6l\u00e7e\u011fi t\u00fcr\u00fcd\u00fcr. Ger\u00e7ek bir s\u0131f\u0131r noktas\u0131 olmamas\u0131 d\u0131\u015f\u0131nda oran \u00f6l\u00e7e\u011fine benzer.<\/p>\n\n\n\n

\u00d6rne\u011fin, Celsius s\u0131cakl\u0131k \u00f6l\u00e7e\u011fi aral\u0131k \u00f6l\u00e7e\u011fine bir \u00f6rnektir. 10\u00b0C ile 20\u00b0C aras\u0131ndaki fark, 20\u00b0C ile 30\u00b0C aras\u0131ndaki farkla ayn\u0131d\u0131r. Bununla birlikte, 0\u00b0C s\u0131cakl\u0131\u011f\u0131n tamamen yoklu\u011funu de\u011fil, \u00f6l\u00e7ek \u00fczerinde belirli bir noktay\u0131 temsil eder.<\/p>\n\n\n\n

Likert \u00d6l\u00e7e\u011fi<\/h3>\n\n\n\n

Likert \u00f6l\u00e7e\u011fi, tutumlar\u0131, g\u00f6r\u00fc\u015fleri veya alg\u0131lar\u0131 \u00f6l\u00e7mek i\u00e7in \"kesinlikle kat\u0131l\u0131yorum\", \"kat\u0131l\u0131yorum\", \"n\u00f6tr\", \"kat\u0131lm\u0131yorum\" ve \"kesinlikle kat\u0131lm\u0131yorum\" gibi bir dizi yan\u0131t se\u00e7ene\u011fi kullanan yayg\u0131n bir s\u0131ral\u0131 veri t\u00fcr\u00fcd\u00fcr. Her bir yan\u0131ta, genellikle 1 ila 5 veya 1 ila 7 aras\u0131nda de\u011fi\u015fen say\u0131sal bir de\u011fer atan\u0131r; daha y\u00fcksek bir de\u011fer daha olumlu veya daha g\u00fc\u00e7l\u00fc bir yan\u0131t\u0131 g\u00f6sterir. Likert \u00f6l\u00e7e\u011fi genellikle anketlerde ve soru formlar\u0131nda belirli y\u00f6ntemler kullan\u0131larak analiz edilebilecek s\u0131ral\u0131 verileri toplamak i\u00e7in kullan\u0131l\u0131r.<\/p>\n\n\n\n

Ordinal Veriler Nas\u0131l Analiz Edilir?<\/strong><\/h2>\n\n\n\n

S\u0131ral\u0131 verileri analiz etmek i\u00e7in a\u015fa\u011f\u0131dakiler de dahil olmak \u00fczere \u00e7e\u015fitli y\u00f6ntemler vard\u0131r:<\/p>\n\n\n\n

Tan\u0131mlay\u0131c\u0131 \u0130statistikler:<\/strong> Tan\u0131mlay\u0131c\u0131 istatistikler, s\u0131ral\u0131 verilerin merkezi e\u011filimini ve da\u011f\u0131l\u0131m\u0131n\u0131 \u00f6zetlemek ve tan\u0131mlamak i\u00e7in kullan\u0131l\u0131r. S\u0131ral\u0131 veriler i\u00e7in yayg\u0131n olarak kullan\u0131lan baz\u0131 tan\u0131mlay\u0131c\u0131 istatistikler medyan, mod ve y\u00fczdelik dilimleri i\u00e7erir. Tan\u0131mlay\u0131c\u0131 istatistikler, verilere genel bir bak\u0131\u015f sa\u011flamaya ve ayk\u0131r\u0131 de\u011ferler veya \u00e7arp\u0131k da\u011f\u0131l\u0131mlar gibi olas\u0131 sorunlar\u0131 belirlemeye yard\u0131mc\u0131 olabilir. Ancak, gruplar aras\u0131ndaki farkl\u0131l\u0131klar\u0131n veya ili\u015fkilerin istatistiksel \u00f6nemi hakk\u0131nda herhangi bir bilgi sa\u011flamazlar.<\/p>\n\n\n\n

Parametrik olmayan testler: <\/strong>Parametrik olmayan testler, verilerin normal da\u011f\u0131l\u0131m gibi belirli bir da\u011f\u0131l\u0131m\u0131 takip etmesini gerektirmedikleri ve kategoriler aras\u0131ndaki aral\u0131klar\u0131n e\u015fit oldu\u011funu varsaymad\u0131klar\u0131 i\u00e7in s\u0131ral\u0131 verileri analiz etmek i\u00e7in yayg\u0131n olarak kullan\u0131l\u0131r. Bu testler, g\u00f6zlemlerin tam de\u011ferleri yerine s\u0131ralamalar\u0131na dayan\u0131r. Parametrik olmayan testler ayk\u0131r\u0131 de\u011ferlere kar\u015f\u0131 dayan\u0131kl\u0131d\u0131r ve parametrik testlerin varsay\u0131mlar\u0131 kar\u015f\u0131lanmad\u0131\u011f\u0131nda s\u0131kl\u0131kla kullan\u0131l\u0131r. Ancak, \u00f6zellikle \u00f6rneklem b\u00fcy\u00fckl\u00fc\u011f\u00fc k\u00fc\u00e7\u00fck oldu\u011funda parametrik testlere g\u00f6re daha az istatistiksel g\u00fcce sahip olabilirler. <\/p>\n\n\n\n

S\u0131ral\u0131 lojistik regresyon:<\/strong> S\u0131ral\u0131 lojistik regresyon, bir veya daha fazla s\u0131ral\u0131 ba\u011f\u0131ms\u0131z de\u011fi\u015fken ile s\u0131ral\u0131 bir ba\u011f\u0131ml\u0131 de\u011fi\u015fken aras\u0131ndaki ili\u015fkiyi modellemek i\u00e7in kullan\u0131lan istatistiksel bir y\u00f6ntemdir. Bu y\u00f6ntem, s\u0131ral\u0131 bir de\u011fi\u015fkenin sonucunu etkileyen fakt\u00f6rleri belirlemek istedi\u011finizde kullan\u0131\u015fl\u0131d\u0131r. Ordinal lojistik regresyon, ba\u011f\u0131ml\u0131 de\u011fi\u015fkenin kategorilerinin s\u0131ral\u0131 oldu\u011funu ve kategoriler aras\u0131ndaki mesafenin mutlaka e\u015fit olmad\u0131\u011f\u0131n\u0131 varsayar. Ayr\u0131ca ba\u011f\u0131ml\u0131 de\u011fi\u015fken ile ba\u011f\u0131ms\u0131z de\u011fi\u015fkenler aras\u0131ndaki ili\u015fkinin log-lineer oldu\u011funu varsayar.<\/p>\n\n\n\n

Yaz\u0131\u015fma analizi:<\/strong> Bu y\u00f6ntem, iki veya daha fazla s\u0131ral\u0131 de\u011fi\u015fken aras\u0131ndaki ili\u015fkiyi ke\u015ffetmek i\u00e7in kullan\u0131l\u0131r. De\u011fi\u015fkenler aras\u0131ndaki \u00f6r\u00fcnt\u00fc ve ili\u015fkilerin belirlenmesine ve bunlar\u0131n iki boyutlu bir uzayda g\u00f6rselle\u015ftirilmesine yard\u0131mc\u0131 olur. Y\u00f6ntem, her bir de\u011fi\u015fken i\u00e7in her bir kategorinin frekanslar\u0131n\u0131 g\u00f6steren bir olas\u0131l\u0131k tablosunun olu\u015fturulmas\u0131n\u0131 i\u00e7erir. Ard\u0131ndan, verilerin genel da\u011f\u0131l\u0131m\u0131na dayal\u0131 olarak her kategori i\u00e7in bir dizi puan hesaplan\u0131r. Bu puanlar, her kategorinin bir nokta ile temsil edildi\u011fi iki boyutlu bir grafik olu\u015fturmak i\u00e7in kullan\u0131l\u0131r. Noktalar aras\u0131ndaki mesafe, kategoriler aras\u0131ndaki benzerlik veya benzemezlik derecesini g\u00f6sterir.<\/p>\n\n\n\n

Yap\u0131sal e\u015fitlik modellemesi:<\/strong> Yap\u0131sal e\u015fitlik modellemesi (YEM), de\u011fi\u015fkenler aras\u0131ndaki ili\u015fkileri analiz etmek ve karma\u015f\u0131k modelleri test etmek i\u00e7in kullan\u0131lan istatistiksel bir y\u00f6ntemdir. Hem g\u00f6zlenen hem de gizli birden fazla de\u011fi\u015fkeni ele alabilen ve de\u011fi\u015fkenler aras\u0131ndaki nedensel ili\u015fkileri test edebilen \u00e7ok de\u011fi\u015fkenli bir analiz tekni\u011fidir. S\u0131ral\u0131 verileri analiz ederken, YEM birden fazla s\u0131ral\u0131 de\u011fi\u015fken ve gizli yap\u0131 i\u00e7eren modelleri test etmek i\u00e7in kullan\u0131labilir. Ayr\u0131ca de\u011fi\u015fkenlerin birbirleri \u00fczerindeki do\u011frudan ve dolayl\u0131 etkilerinin b\u00fcy\u00fckl\u00fc\u011f\u00fcn\u00fcn belirlenmesine ve tahmin edilmesine de yard\u0131mc\u0131 olabilir.<\/p>\n\n\n\n

\u00c7\u0131kar\u0131msal \u0130statistik<\/strong><\/h2>\n\n\n\n

\u00c7\u0131kar\u0131msal istatistik, bir veri \u00f6rne\u011fine dayanarak bir pop\u00fclasyon hakk\u0131nda sonu\u00e7lar \u00e7\u0131karmay\u0131 ve \u00e7\u0131kar\u0131mlarda bulunmay\u0131 i\u00e7eren bir istatistik dal\u0131d\u0131r. Ara\u015ft\u0131rmac\u0131lar\u0131n g\u00f6zlemlenen verilerin \u00f6tesinde daha b\u00fcy\u00fck bir grup hakk\u0131nda genellemeler, tahminler ve hipotezler yapmas\u0131na olanak tan\u0131yan g\u00fc\u00e7l\u00fc bir ara\u00e7t\u0131r.<\/p>\n\n\n\n

Tan\u0131mlay\u0131c\u0131 istatistikler verileri \u00f6zetler ve tan\u0131mlarken, \u00e7\u0131kar\u0131msal istatistikler \u00f6rneklem verilerini analiz etmek ve \u00f6rneklemin al\u0131nd\u0131\u011f\u0131 pop\u00fclasyon hakk\u0131nda sonu\u00e7lar \u00e7\u0131karmak i\u00e7in olas\u0131l\u0131k teorisi ve istatistiksel y\u00f6ntemler kullanarak bir ad\u0131m daha ileri gider. \u00c7\u0131kar\u0131msal istatistikleri kullanarak ara\u015ft\u0131rmac\u0131lar tahminlerde bulunabilir, hipotezleri test edebilir ve bulgulara dayanarak bilin\u00e7li kararlar verebilir.<\/p>\n\n\n\n

Ordinal Verilerin Kullan\u0131m Alanlar\u0131<\/strong><\/h2>\n\n\n\n

S\u0131ral\u0131 veriler \u00e7ok \u00e7e\u015fitli uygulamalarda kullan\u0131l\u0131r ve genellikle anketler, soru formlar\u0131 ve di\u011fer ara\u015ft\u0131rma bi\u00e7imleri yoluyla toplan\u0131r. \u0130\u015fte s\u0131ral\u0131 verilerin baz\u0131 yayg\u0131n kullan\u0131mlar\u0131:<\/p>\n\n\n\n

Anketler \/ Soru Formlar\u0131<\/h3>\n\n\n\n

Anketler ve soru formlar\u0131 s\u0131ral\u0131 veri toplaman\u0131n yayg\u0131n bir yoludur. \u00d6rne\u011fin, bir anket kat\u0131l\u0131mc\u0131lardan bir ifadeye kat\u0131lma d\u00fczeylerini \"kesinlikle kat\u0131lm\u0131yorum\" ile \"kesinlikle kat\u0131l\u0131yorum\" aras\u0131nda bir \u00f6l\u00e7ekte derecelendirmelerini isteyebilir. Bu t\u00fcr veriler daha sonra yan\u0131tlardaki e\u011filimleri veya kal\u0131plar\u0131 analiz etmek i\u00e7in kullan\u0131labilir.<\/p>\n\n\n\n

Ara\u015ft\u0131rma<\/h3>\n\n\n\n

S\u0131ral\u0131 veriler, ara\u015ft\u0131rma \u00e7al\u0131\u015fmalar\u0131nda farkl\u0131 de\u011fi\u015fkenler aras\u0131ndaki ili\u015fkiyi \u00f6l\u00e7mek i\u00e7in de kullan\u0131labilir. \u00d6rne\u011fin, bir ara\u015ft\u0131rmac\u0131 belirli bir hastal\u0131\u011f\u0131 olan bir grup hastada belirli bir semptomun \u015fiddetini \u00f6l\u00e7mek i\u00e7in s\u0131ral\u0131 bir \u00f6l\u00e7ek kullanabilir. Bu t\u00fcr veriler daha sonra farkl\u0131 hasta gruplar\u0131nda semptomun \u015fiddetini kar\u015f\u0131la\u015ft\u0131rmak veya zaman i\u00e7inde semptomdaki de\u011fi\u015fiklikleri izlemek i\u00e7in kullan\u0131labilir.<\/p>\n\n\n\n

M\u00fc\u015fteri Hizmetleri<\/h3>\n\n\n\n

S\u0131ral\u0131 veriler m\u00fc\u015fteri hizmetlerinde m\u00fc\u015fteri memnuniyetini veya memnuniyetsizli\u011fini \u00f6l\u00e7mek i\u00e7in de kullan\u0131labilir. \u00d6rne\u011fin, bir m\u00fc\u015fteriden bir \u015firketin \u00fcr\u00fcn veya hizmetiyle ilgili deneyimlerini \"hi\u00e7 memnun de\u011filim\" ile \"\u00e7ok memnunum\" aras\u0131nda bir \u00f6l\u00e7ekte derecelendirmesi istenebilir. Bu t\u00fcr veriler daha sonra iyile\u015ftirme alanlar\u0131n\u0131 belirlemek ve zaman i\u00e7inde m\u00fc\u015fteri memnuniyetindeki de\u011fi\u015fiklikleri izlemek i\u00e7in kullan\u0131labilir.<\/p>\n\n\n\n

\u0130\u015f ba\u015fvurular\u0131<\/h3>\n\n\n\n

S\u0131ral\u0131 veriler, i\u015f ba\u015fvurular\u0131nda bir ba\u015fvuru sahibinin niteliklerini veya deneyim d\u00fczeyini \u00f6l\u00e7mek i\u00e7in de kullan\u0131labilir. \u00d6rne\u011fin, bir i\u015fveren i\u015f ba\u015fvurusunda bulunan adaylardan belirli bir alandaki deneyim d\u00fczeylerini \"deneyim yok\" ile \"uzman\" aras\u0131nda bir \u00f6l\u00e7ekte derecelendirmelerini isteyebilir. Bu t\u00fcr veriler daha sonra farkl\u0131 i\u015f ba\u015fvuru sahiplerinin niteliklerini kar\u015f\u0131la\u015ft\u0131rmak ve i\u015f i\u00e7in en nitelikli aday\u0131 se\u00e7mek i\u00e7in kullan\u0131labilir.<\/p>\n\n\n\n

Ordinal ve Nominal Veriler Aras\u0131ndaki Fark<\/strong><\/h2>\n\n\n\n

S\u0131ral\u0131 ve nominal veriler iki kategorik veri t\u00fcr\u00fcd\u00fcr. Aralar\u0131ndaki temel fark, \u00f6l\u00e7\u00fcm seviyesinde ve aktard\u0131klar\u0131 bilgide yatmaktad\u0131r.<\/p>\n\n\n\n

S\u0131ral\u0131 veriler, de\u011fi\u015fkenlerin do\u011fal bir s\u0131raya veya s\u0131ralamaya sahip oldu\u011fu bir kategorik veri t\u00fcr\u00fcd\u00fcr. S\u0131ra d\u00fczeyinde \u00f6l\u00e7\u00fcl\u00fcr, yani do\u011fal bir s\u0131ralamaya sahiptir, ancak de\u011ferler aras\u0131ndaki farklar \u00f6l\u00e7\u00fclemez veya \u00f6l\u00e7\u00fclemez. S\u0131ral\u0131 verilere \u00f6rnek olarak s\u0131ralamalar, derecelendirmeler ve Likert \u00f6l\u00e7ekleri verilebilir.<\/p>\n\n\n\n

\u00d6te yandan, nominal veriler de bir kategorik veri t\u00fcr\u00fcd\u00fcr, ancak do\u011fal bir s\u0131ralama veya d\u00fczene sahip de\u011fildir. Nominal d\u00fczeyde \u00f6l\u00e7\u00fcl\u00fcr, yani veriler herhangi bir do\u011fal s\u0131ralama veya d\u00fczen olmaks\u0131z\u0131n yaln\u0131zca birbirini d\u0131\u015flayan kategoriler halinde s\u0131n\u0131fland\u0131r\u0131labilir. Nominal verilere \u00f6rnek olarak cinsiyet, etnik k\u00f6ken ve medeni durum verilebilir.<\/p>\n\n\n\n

S\u0131ral\u0131 ve nominal veriler aras\u0131ndaki temel fark, s\u0131ral\u0131 verilerin do\u011fal bir d\u00fczene veya s\u0131ralamaya sahip olmas\u0131, nominal verilerin ise olmamas\u0131d\u0131r. S\u0131ral\u0131 ve nominal veriler aras\u0131ndaki fark hakk\u0131nda daha fazla bilgi edinmek i\u00e7in bu web sitesi.<\/a><\/p>\n\n\n\n

\u00c7ok \u00f6zel bir ill\u00fcstrasyona m\u0131 ihtiyac\u0131n\u0131z var? Sizin i\u00e7in tasarlayal\u0131m!<\/strong><\/h2>\n\n\n\n

Mind the Graph<\/a> platformu, karma\u015f\u0131k bilimsel kavramlar\u0131 ve ihtiya\u00e7 duydu\u011funuz \u00f6zel g\u00f6rselleri i\u00e7eren geni\u015f bir bilimsel ill\u00fcstrasyon ve \u015fablon k\u00fct\u00fcphanesi sunar. Mind the Graph, beklentilerinizi kar\u015f\u0131layan y\u00fcksek kaliteli bir ill\u00fcstrasyon olu\u015fturmak i\u00e7in sizinle birlikte \u00e7al\u0131\u015facakt\u0131r. Bu hizmet, \u00f6zel tasar\u0131m yaz\u0131l\u0131mlar\u0131na veya becerilerine ihtiya\u00e7 duymadan ara\u015ft\u0131rman\u0131z, sunumunuz veya yay\u0131n\u0131n\u0131z i\u00e7in tam olarak ihtiyac\u0131n\u0131z olan g\u00f6rsellere sahip olman\u0131z\u0131 sa\u011flar.<\/p>\n\n\n\n

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\"\"<\/a><\/figure><\/div>\n\n\n
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Mind the Graph ile Yaratmaya Ba\u015flay\u0131n<\/a><\/div>\n<\/div>\n\n\n\n
<\/div>","protected":false},"excerpt":{"rendered":"

Burada s\u0131ral\u0131 veri \u00f6rnekleri hakk\u0131nda kapsaml\u0131 bir anlay\u0131\u015f edinin. S\u0131ral\u0131 verilerin ne oldu\u011fu ve etkili bir \u015fekilde nas\u0131l kullan\u0131laca\u011f\u0131 hakk\u0131nda bilgi edinin.<\/p>","protected":false},"author":35,"featured_media":29894,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[959,28],"tags":[],"yoast_head":"\nExploring Ordinal Data: Examples and Uses - Mind the Graph Blog<\/title>\n<meta name=\"description\" content=\"Get a comprehensive understanding of ordinal data examples here. Learn about what ordinal data is, and how to use it in an effective way.\" \/>\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\/tr\/sirali-veri-ornekleri\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Exploring Ordinal Data: Examples and Uses\" \/>\n<meta property=\"og:description\" content=\"Get a comprehensive understanding of ordinal data examples here. 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