{"id":55803,"date":"2024-12-12T09:00:00","date_gmt":"2024-12-12T12:00:00","guid":{"rendered":"https:\/\/mindthegraph.com\/blog\/?p=55803"},"modified":"2024-12-09T14:05:01","modified_gmt":"2024-12-09T17:05:01","slug":"chi-square-test","status":"publish","type":"post","link":"https:\/\/mindthegraph.com\/blog\/tr\/chi-square-test\/","title":{"rendered":"Ki-kare Testi: Bu \u0130statistiksel Arac\u0131 Anlamak ve Uygulamak"},"content":{"rendered":"<p>Ki-kare testi, \u00f6zellikle \u00e7e\u015fitli form ve disiplinlerdeki kategorik verileri analiz etmek i\u00e7in istatistikte g\u00fc\u00e7l\u00fc bir ara\u00e7t\u0131r. Baz\u0131 veri k\u00fcmelerinde s\u00fcrekli say\u0131lar verileri temsil ederken, di\u011ferlerinde kategorik veriler cinsiyet, tercihler veya e\u011fitim d\u00fczeyine g\u00f6re grupland\u0131r\u0131lm\u0131\u015f verileri temsil eder. Kategorik verileri analiz ederken ki-kare testi, ili\u015fkileri ke\u015ffetmek ve anlaml\u0131 i\u00e7g\u00f6r\u00fcler elde etmek i\u00e7in yayg\u0131n olarak kullan\u0131lan istatistiksel bir ara\u00e7t\u0131r. Bu makale ki-kare testinin nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131, uygulamalar\u0131n\u0131 ve ara\u015ft\u0131rmac\u0131lar ve veri analistleri i\u00e7in neden gerekli oldu\u011funu incelemektedir.<\/p>\n\n\n\n<p>Bu blog boyunca Ki-kare testinin nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131, nas\u0131l yap\u0131ld\u0131\u011f\u0131n\u0131 ve nas\u0131l yorumlanabilece\u011fini inceleyece\u011fiz. \u0130ster \u00f6\u011frenci ister ara\u015ft\u0131rmac\u0131 olun ya da genel olarak veri analiziyle ilgileniyor olun, veri analizini daha iyi anlamak i\u00e7in Ki-kare testini kullanabilirsiniz.<\/p>\n\n\n\n<h2>Ki-kare Testinin \u00d6nemini Anlamak<\/h2>\n\n\n\n<p>Ki-kare testi, kategorik de\u011fi\u015fkenler aras\u0131ndaki ili\u015fkileri incelemek ve \u00e7e\u015fitli alanlardaki hipotezleri test etmek i\u00e7in kullan\u0131lan temel bir istatistiksel y\u00f6ntemdir. Ki-kare testinin nas\u0131l uygulanaca\u011f\u0131n\u0131 anlamak, ara\u015ft\u0131rmac\u0131lar\u0131n verilerindeki \u00f6nemli kal\u0131plar\u0131 ve ili\u015fkileri belirlemelerine yard\u0131mc\u0131 olabilir. S\u0131f\u0131r hipotezi alt\u0131nda, g\u00f6zlemlenen verileri, de\u011fi\u015fkenler aras\u0131nda bir ili\u015fki olmasayd\u0131 bekledi\u011fimizle kar\u015f\u0131la\u015ft\u0131r\u0131r. Biyoloji, pazarlama ve sosyal bilimler gibi alanlarda, bu test \u00f6zellikle n\u00fcfus da\u011f\u0131l\u0131mlar\u0131 hakk\u0131ndaki hipotezleri test etmek i\u00e7in kullan\u0131\u015fl\u0131d\u0131r.<\/p>\n\n\n\n<p>Ki-kare testi \u00f6z\u00fcnde kategorik verilerde g\u00f6zlenen ve beklenen frekanslar aras\u0131ndaki uyu\u015fmazl\u0131\u011f\u0131 \u00f6l\u00e7er. Bunu kullanarak a\u015fa\u011f\u0131daki gibi sorular\u0131 yan\u0131tlayabiliriz: \"G\u00f6zlenen veri kal\u0131plar\u0131 \u015fans eseri beklenenden farkl\u0131 m\u0131?\" veya \"\u0130ki kategorik de\u011fi\u015fken birbirinden ba\u011f\u0131ms\u0131z m\u0131?\"<\/p>\n\n\n\n<h3>Ki-kare Testlerinin T\u00fcrleri<\/h3>\n\n\n\n<p>Ki-kare testinin iki temel formu vard\u0131r - uyum iyili\u011fi ve ba\u011f\u0131ms\u0131zl\u0131k testleri - her biri belirli istatistiksel sorgulamalar i\u00e7in uyarlanm\u0131\u015ft\u0131r.<\/p>\n\n\n\n<p><strong>1. Ki-kare Uyum \u0130yili\u011fi Testi<\/strong><\/p>\n\n\n\n<p>Bireysel bir kategorik de\u011fi\u015fkenin belirli bir da\u011f\u0131l\u0131m\u0131 takip edip etmedi\u011fini belirlemek i\u00e7in test edilir. G\u00f6zlenen verilerin beklenen bir da\u011f\u0131l\u0131ma uyup uymad\u0131\u011f\u0131n\u0131 kontrol etmek i\u00e7in genellikle bir model veya ge\u00e7mi\u015f veriler kullan\u0131l\u0131r.<\/p>\n\n\n\n<figure class=\"wp-block-image alignwide size-full\"><a href=\"https:\/\/mindthegraph.com\/science-figures\/?utm_source=blog&amp;utm_medium=cta-final&amp;utm_campaign=conversion\"><img decoding=\"async\" loading=\"lazy\" width=\"651\" height=\"174\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/06\/mind-the-graph-1.png\" alt=\"Ara\u015ft\u0131rmac\u0131lar ve e\u011fitimciler i\u00e7in bilimsel ill\u00fcstrasyonlar ve g\u00f6rseller olu\u015fturmaya y\u00f6nelik bir platform olan Mind the Graph&#039;nin logosu.\" class=\"wp-image-54660\" srcset=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/06\/mind-the-graph-1.png 651w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/06\/mind-the-graph-1-300x80.png 300w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/06\/mind-the-graph-1-18x5.png 18w, https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2024\/06\/mind-the-graph-1-100x27.png 100w\" sizes=\"(max-width: 651px) 100vw, 651px\" \/><\/a><figcaption class=\"wp-element-caption\">Mind the Graph - <a href=\"https:\/\/mindthegraph.com\/science-figures\/?utm_source=blog&amp;utm_medium=cta-final&amp;utm_campaign=conversion\">\u0130lgi \u00c7ekici Bilimsel \u00c7izimler Olu\u015fturun.<\/a><\/figcaption><\/figure>\n\n\n\n<p>Bir zar\u0131 60 kez yuvarlad\u0131\u011f\u0131n\u0131z\u0131 d\u00fc\u015f\u00fcn\u00fcn. Zar adil oldu\u011fundan, her bir taraf\u0131n on kez g\u00f6r\u00fcnmesini beklersiniz, ancak ger\u00e7ek sonu\u00e7lar biraz farkl\u0131l\u0131k g\u00f6sterir. Bu sapman\u0131n \u00f6nemli mi yoksa sadece \u015fans eseri mi oldu\u011funu belirlemek i\u00e7in uyum iyili\u011fi testini uygulayabilirsiniz.<\/p>\n\n\n\n<p><strong>\u0130lgili Ad\u0131mlar:<\/strong><\/p>\n\n\n\n<ol>\n<li>Teorik da\u011f\u0131l\u0131ma dayanarak, beklenen frekanslar\u0131 belirleyin.<\/li>\n\n\n\n<li>Daha sonra bunlar\u0131 g\u00f6zlemlenen frekanslarla kar\u015f\u0131la\u015ft\u0131r\u0131n.<\/li>\n\n\n\n<li>Sapmay\u0131 \u00f6l\u00e7mek i\u00e7in Ki-kare istatisti\u011fini hesaplay\u0131n.<\/li>\n<\/ol>\n\n\n\n<p>Ara\u015ft\u0131rmac\u0131lar bu testi genellikle kalite kontrol, genetik ve g\u00f6zlemlenen verileri teorik bir da\u011f\u0131l\u0131mla kar\u015f\u0131la\u015ft\u0131rmak istedikleri di\u011fer alanlarda kullan\u0131rlar.<\/p>\n\n\n\n<p><strong>2. Ki-kare Ba\u011f\u0131ms\u0131zl\u0131k Testi<\/strong><\/p>\n\n\n\n<p>Bu testte, iki kategorik de\u011fi\u015fkenin ba\u011f\u0131ms\u0131zl\u0131\u011f\u0131 de\u011ferlendirilir. Bu test, bir de\u011fi\u015fkenin da\u011f\u0131l\u0131m\u0131n\u0131n ikinci bir de\u011fi\u015fkenin seviyelerine g\u00f6re de\u011fi\u015fip de\u011fi\u015fmedi\u011fini inceler. De\u011fi\u015fkenlerin frekans da\u011f\u0131l\u0131mlar\u0131n\u0131 g\u00f6steren olas\u0131l\u0131k tablolar\u0131 tipik olarak Ki-kare testi kullan\u0131larak ba\u011f\u0131ms\u0131zl\u0131k a\u00e7\u0131s\u0131ndan test edilir.<\/p>\n\n\n\n<p>Kat\u0131l\u0131mc\u0131lara cinsiyetlerini ve tercih ettikleri film t\u00fcr\u00fcn\u00fc (aksiyon, drama, komedi) soran bir anket yapt\u0131\u011f\u0131n\u0131z\u0131 varsayal\u0131m. Cinsiyetin film tercihlerini etkileyip etkilemedi\u011fini veya ba\u011f\u0131ms\u0131z olup olmad\u0131klar\u0131n\u0131 belirlemek i\u00e7in Ki-kare ba\u011f\u0131ms\u0131zl\u0131k testi kullan\u0131labilir.<\/p>\n\n\n\n<p><strong>\u0130lgili Ad\u0131mlar:<\/strong><\/p>\n\n\n\n<ol>\n<li>\u0130ki de\u011fi\u015fken i\u00e7in bir olumsall\u0131k tablosu olu\u015fturun.<\/li>\n\n\n\n<li>De\u011fi\u015fkenlerin ba\u011f\u0131ms\u0131z oldu\u011fu varsay\u0131m\u0131na dayanarak, beklenen frekanslar\u0131 hesaplay\u0131n.<\/li>\n\n\n\n<li>Ki-kare istatisti\u011fini kullanarak, g\u00f6zlenen frekanslar\u0131 beklenen frekanslarla kar\u015f\u0131la\u015ft\u0131r\u0131n.<\/li>\n<\/ol>\n\n\n\n<p>Pazar ara\u015ft\u0131rmas\u0131, sa\u011fl\u0131k ve e\u011fitim alanlar\u0131nda bu test, e\u011fitim d\u00fczeyi ve oy verme tercihleri aras\u0131ndaki ili\u015fki gibi demografik de\u011fi\u015fkenler ve sonu\u00e7lar aras\u0131ndaki ili\u015fkiyi incelemek i\u00e7in yayg\u0131n olarak kullan\u0131lmaktad\u0131r.<\/p>\n\n\n\n<h2>Ger\u00e7ek D\u00fcnya Senaryolar\u0131nda Ki-kare Testi Uygulamalar\u0131<\/h2>\n\n\n\n<p>Ki-kare testi \u00f6zellikle cinsiyet, tercihler veya siyasi e\u011filimler gibi kategorik verilerle \u00e7al\u0131\u015f\u0131rken ili\u015fkileri ve \u00f6r\u00fcnt\u00fcleri test etmek i\u00e7in kullan\u0131\u015fl\u0131d\u0131r. Ba\u011f\u0131ms\u0131zl\u0131k ve uyum iyili\u011fi testleri, iki de\u011fi\u015fken aras\u0131nda anlaml\u0131 bir ili\u015fki olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in kullan\u0131l\u0131r (ba\u011f\u0131ms\u0131zl\u0131k testi).<\/p>\n\n\n\n<p>Ara\u015ft\u0131rmac\u0131lar kategorik verilerde Ki-kare testini kullanarak hipotezleri test edebilir ve \u00f6r\u00fcnt\u00fcleri belirleyebilirler. Yayg\u0131n olarak benimsenmesinin birka\u00e7 nedeni vard\u0131r:<\/p>\n\n\n\n<ul>\n<li>Parametrik testlerin aksine, verilerin alt\u0131nda yatan da\u011f\u0131l\u0131m hakk\u0131nda varsay\u0131mlar gerektirmez.<\/li>\n\n\n\n<li>\u00c7e\u015fitli disiplinler kullanabilir, bu da onu \u00e7ok y\u00f6nl\u00fc hale getirir.<\/li>\n\n\n\n<li>G\u00f6zlemlenen modellere dayanarak, bilin\u00e7li kararlar al\u0131nmas\u0131na yard\u0131mc\u0131 olur.<\/li>\n<\/ul>\n\n\n\n<h2>Ki-kare Testinin Varsay\u0131mlar\u0131<\/h2>\n\n\n\n<p>Ki-kare testi sonu\u00e7lar\u0131n\u0131n ge\u00e7erlili\u011fini sa\u011flamak i\u00e7in belirli varsay\u0131mlar\u0131n kar\u015f\u0131lanmas\u0131 gerekir. Bu varsay\u0131mlar, \u00f6zellikle kategorik verilerle \u00e7al\u0131\u015f\u0131rken testin do\u011frulu\u011funu ve uygunlu\u011funu korumaya yard\u0131mc\u0131 olur. \u00dc\u00e7 temel varsay\u0131m\u0131n ele al\u0131nmas\u0131 gerekir: rastgele \u00f6rnekleme, kategorik de\u011fi\u015fkenler ve beklenen frekans say\u0131lar\u0131.<\/p>\n\n\n\n<p><strong>1. Rastgele \u00d6rnekleme<\/strong><\/p>\n\n\n\n<p>\u0130lk ve en temel varsay\u0131m olarak veriler rastgele \u00f6rnekleme yoluyla toplanmal\u0131d\u0131r. Sonu\u00e7 olarak, \u00f6rneklem her bir bireyi veya unsuru e\u015fit olarak i\u00e7erir. Rastgele bir \u00f6rneklem \u00f6nyarg\u0131y\u0131 en aza indirir, b\u00f6ylece sonu\u00e7lar daha b\u00fcy\u00fck bir pop\u00fclasyona genellenebilir.<\/p>\n\n\n\n<p>\u00d6rneklem rastgele de\u011filse, sonu\u00e7lar \u00e7arp\u0131k olabilir ve yanl\u0131\u015f sonu\u00e7lara yol a\u00e7abilir. Bir pop\u00fclasyon i\u00e7inde yaln\u0131zca belirli bir gruba da\u011f\u0131t\u0131lan bir anketin sonu\u00e7lar\u0131 t\u00fcm kurulu\u015fun g\u00f6r\u00fc\u015flerini yans\u0131tmayabilir, dolay\u0131s\u0131yla rastgele \u00f6rnekleme varsay\u0131m\u0131 ihlal edilmi\u015f olur.<\/p>\n\n\n\n<p><strong>2. Kategorik De\u011fi\u015fkenler<\/strong><\/p>\n\n\n\n<p>Kategorik de\u011fi\u015fkenlerin (farkl\u0131 kategorilere ayr\u0131labilen veriler) analiz edilmesi Ki-kare testinin amac\u0131d\u0131r. Say\u0131sal de\u011fi\u015fkenler olmamal\u0131 (kolayl\u0131k sa\u011flamak i\u00e7in say\u0131sal olarak kodlanabilmelerine ra\u011fmen) ve a\u00e7\u0131k\u00e7a tan\u0131mlanm\u0131\u015f gruplar halinde grupland\u0131r\u0131lmal\u0131d\u0131r.<\/p>\n\n\n\n<p>Kategorik de\u011fi\u015fkenlere \u00f6rnek olarak \u015funlar verilebilir:<\/p>\n\n\n\n<ul>\n<li>Cinsiyet (erkek, kad\u0131n, ikili olmayan)<\/li>\n\n\n\n<li>Medeni durum (bekar, evli, bo\u015fanm\u0131\u015f)<\/li>\n\n\n\n<li>G\u00f6z rengi (mavi, kahverengi, ye\u015fil)<\/li>\n<\/ul>\n\n\n\n<p>Ki-kare testi, kategorilere d\u00f6n\u00fc\u015ft\u00fcr\u00fclmedikleri s\u00fcrece boy veya kilo gibi s\u00fcrekli verilerle do\u011frudan kullan\u0131lamaz. Ki-kare testinin anlaml\u0131 olabilmesi i\u00e7in verilerin \"k\u0131sa\", \"ortalama\" veya \"uzun\" gibi kategorik olmas\u0131 gerekir.<\/p>\n\n\n\n<p><strong>3. Beklenen Frekans Say\u0131s\u0131<\/strong><\/p>\n\n\n\n<p>Ki-kare testinin bir di\u011fer kritik varsay\u0131m\u0131, olas\u0131l\u0131k tablosundaki kategorilerin veya h\u00fccrelerin beklenen s\u0131kl\u0131\u011f\u0131d\u0131r. S\u0131f\u0131r hipotezinin do\u011fru oldu\u011fu (yani de\u011fi\u015fkenlerin ili\u015fkili olmad\u0131\u011f\u0131) varsay\u0131ld\u0131\u011f\u0131nda, beklenen frekans her bir kategoride var olan teorik frekans say\u0131s\u0131d\u0131r.&nbsp;<\/p>\n\n\n\n<p>Temel kural \u015fudur: Her h\u00fccre i\u00e7in beklenen frekans en az 5 olmal\u0131d\u0131r. Beklenen frekans\u0131n d\u00fc\u015f\u00fck olmas\u0131, test istatisti\u011finin bozulmas\u0131 halinde g\u00fcvenilir olmayan sonu\u00e7lara yol a\u00e7abilir. Beklenen frekanslar 5'in alt\u0131na d\u00fc\u015ft\u00fc\u011f\u00fcnde, \u00f6zellikle de k\u00fc\u00e7\u00fck \u00f6rneklem boyutlar\u0131nda Fisher's Exact Test dikkate al\u0131nmal\u0131d\u0131r.<\/p>\n\n\n\n<h2>Ki-kare Testi Yapmak \u0130\u00e7in Ad\u0131m Ad\u0131m K\u0131lavuz<\/h2>\n\n\n\n<ol>\n<li>Hipotezlerin Kurulmas\u0131 (Null ve Alternatif)<\/li>\n<\/ol>\n\n\n\n<ul>\n<li>Bo\u015f Hipotez (H0): Kar\u015f\u0131la\u015ft\u0131rd\u0131\u011f\u0131n\u0131z iki \u015fey aras\u0131nda hi\u00e7bir ba\u011flant\u0131 yoktur. G\u00f6rd\u00fc\u011f\u00fcn\u00fcz t\u00fcm farkl\u0131l\u0131klar rastlant\u0131sald\u0131r.<\/li>\n\n\n\n<li>Alternatif Hipotez (H\u2081): Bu, iki \u015fey aras\u0131nda ger\u00e7ek bir ba\u011flant\u0131 oldu\u011fu anlam\u0131na gelir. Farkl\u0131l\u0131klar rastgele de\u011fil, anlaml\u0131d\u0131r.<\/li>\n<\/ul>\n\n\n\n<h3>2. Beklenmedik Durum Tablosunun Olu\u015fturulmas\u0131<\/h3>\n\n\n\n<p>Olas\u0131l\u0131k tablolar\u0131, belirli \u015feylerin birlikte ne s\u0131kl\u0131kla meydana geldi\u011fini g\u00f6sterir. \u00d6rne\u011fin bu tabloda farkl\u0131 gruplar (erkekler ve kad\u0131nlar gibi) ve farkl\u0131 se\u00e7enekler (hangi \u00fcr\u00fcn\u00fc tercih ettikleri gibi) g\u00f6sterilmektedir. Tabloya bakt\u0131\u011f\u0131n\u0131zda, her bir gruba ve se\u00e7ene\u011fe ka\u00e7 ki\u015finin girdi\u011fini g\u00f6receksiniz.<\/p>\n\n\n\n<h3>3. Beklenen Frekanslar\u0131n Hesaplanmas\u0131<\/h3>\n\n\n\n<p>Kar\u015f\u0131la\u015ft\u0131rd\u0131\u011f\u0131n\u0131z \u015feyler aras\u0131nda ger\u00e7ek bir ba\u011flant\u0131 olmasayd\u0131, beklenen frekanslar bekledi\u011finiz gibi olurdu. Bunlar\u0131 hesaplamak i\u00e7in basit bir form\u00fcl kullan\u0131labilir:<\/p>\n\n\n\n<p>Beklenen Frekans = (Sat\u0131r Toplam\u0131 \u00d7 S\u00fctun Toplam\u0131) \/ Genel Toplam<\/p>\n\n\n\n<p>Bu sadece her \u015fey rastgele olsayd\u0131 say\u0131lar\u0131n nas\u0131l g\u00f6r\u00fcnmesi gerekti\u011fini s\u00f6yler.<\/p>\n\n\n\n<h3>4. Ki-kare \u0130statisti\u011finin Hesaplanmas\u0131<\/h3>\n\n\n\n<p>Ki-kare testi, g\u00f6zlemlenen verilerinizin beklenen sonu\u00e7lardan ne kadar sapt\u0131\u011f\u0131n\u0131 \u00f6l\u00e7menize olanak tan\u0131yarak ili\u015fkilerin var olup olmad\u0131\u011f\u0131n\u0131 belirlemenize yard\u0131mc\u0131 olur. Karma\u015f\u0131k g\u00f6r\u00fcnse de ger\u00e7ek say\u0131lar\u0131 beklenenlerle kar\u015f\u0131la\u015ft\u0131r\u0131r:<\/p>\n\n\n\n<p>\ud835\udf122=\u2211(G\u00f6zlenen-Beklenen)2\/ Beklenen<\/p>\n\n\n\n<p>Bunu tablonuzdaki her kutu i\u00e7in yapars\u0131n\u0131z ve sonra hepsini toplayarak tek bir say\u0131 elde edersiniz, bu da Ki-kare istatisti\u011finizdir.<\/p>\n\n\n\n<h3>5. Serbestlik Derecelerinin Belirlenmesi<\/h3>\n\n\n\n<p>Sonu\u00e7lar\u0131n\u0131z\u0131 yorumlamak i\u00e7in serbestlik derecelerini bilmeniz gerekir. Tablonuzun boyutuna ba\u011fl\u0131 olarak bunlar\u0131 hesaplars\u0131n\u0131z. \u0130\u015fte form\u00fcl:<\/p>\n\n\n\n<p>Serbestlik Derecesi = ( Sat\u0131r Say\u0131s\u0131 -1)\u00d7(S\u00fctun Say\u0131s\u0131-1)<\/p>\n\n\n\n<p>Bu, verilerinizin boyutunu hesaplaman\u0131n s\u00fcsl\u00fc bir yoludur.<\/p>\n\n\n\n<h3>6. P-de\u011ferini Bulmak i\u00e7in Ki-kare Da\u011f\u0131l\u0131m\u0131n\u0131 Kullanma<\/h3>\n\n\n\n<p>Ki-kare istatisti\u011fi ve serbestlik derecesi kullan\u0131larak bir p-de\u011feri hesaplanabilir. P-de\u011ferine bakt\u0131\u011f\u0131n\u0131zda, g\u00f6zlemledi\u011finiz farkl\u0131l\u0131klar\u0131n muhtemelen \u015fansa m\u0131 ba\u011fl\u0131 oldu\u011funu yoksa anlaml\u0131 olup olmad\u0131\u011f\u0131n\u0131 belirleyebilirsiniz.<\/p>\n\n\n\n<p>P-de\u011ferinin yorumlanmas\u0131:<\/p>\n\n\n\n<ul>\n<li>Genellikle k\u00fc\u00e7\u00fck bir p-de\u011feri, buldu\u011funuz farkl\u0131l\u0131klar\u0131n rastgele olmad\u0131\u011f\u0131n\u0131 g\u00f6sterir, bu nedenle s\u0131f\u0131r hipotezini reddedersiniz. \u00c7al\u0131\u015ft\u0131\u011f\u0131n\u0131z \u015fey ile yapt\u0131\u011f\u0131n\u0131z \u015fey aras\u0131nda ger\u00e7ek bir ba\u011flant\u0131 g\u00f6rebilirsiniz.<\/li>\n\n\n\n<li>P-de\u011ferinin 0,05'ten b\u00fcy\u00fck olmas\u0131 farklar\u0131n muhtemelen rastgele oldu\u011funu g\u00f6sterir, bu nedenle s\u0131f\u0131r hipotezini korumal\u0131s\u0131n\u0131z. Bu nedenle, ikisi aras\u0131nda ger\u00e7ek bir ba\u011flant\u0131 yoktur.<\/li>\n<\/ul>\n\n\n\n<p>\u0130ki \u015fey tesad\u00fcfen meydana gelirse veya birbiriyle ili\u015fkiliyse, ba\u011flant\u0131l\u0131 olup olmad\u0131klar\u0131n\u0131 belirlemek i\u00e7in bu basitle\u015ftirilmi\u015f s\u00fcreci kullanabilirsiniz!<\/p>\n\n\n\n<h2>Ki-kare Testinden Elde Edilen Sonu\u00e7lar\u0131n Yorumlanmas\u0131<\/h2>\n\n\n\n<p>Ki-kare istatisti\u011fi bize ger\u00e7ek verilerin (g\u00f6zlemlediklerinizin) kategoriler aras\u0131nda bir ili\u015fki olmasayd\u0131 bekledi\u011fimizden ne kadar farkl\u0131 oldu\u011funu s\u00f6yler. Esasen, g\u00f6zlemledi\u011fimiz sonu\u00e7lar\u0131n \u015fans eseri tahmin etti\u011fimizden ne kadar farkl\u0131 oldu\u011funu \u00f6l\u00e7er.<\/p>\n\n\n\n<ul>\n<li>B\u00fcy\u00fck Ki-kare de\u011feri: Beklentiniz ile ger\u00e7ek aras\u0131ndaki fark b\u00fcy\u00fckt\u00fcr. Verilerinizde ilgin\u00e7 bir \u015feyler oldu\u011funu g\u00f6sterebilir.<\/li>\n\n\n\n<li>K\u00fc\u00e7\u00fck Ki-kare de\u011feri: Bu, g\u00f6zlemlenen verilerin beklenene olduk\u00e7a yak\u0131n oldu\u011fu ve ola\u011fand\u0131\u015f\u0131 bir \u015fey olmayabilece\u011fi anlam\u0131na gelir.<\/li>\n<\/ul>\n\n\n\n<p>Bu do\u011fru olsa da, Ki-kare de\u011feri tek ba\u015f\u0131na size ihtiyac\u0131n\u0131z olan t\u00fcm bilgiyi sa\u011flamaz. Bir p-de\u011feri kullanarak, bir fark\u0131n anlaml\u0131 m\u0131 yoksa sadece bir tesad\u00fcf m\u00fc oldu\u011funu belirleyebilirsiniz.<\/p>\n\n\n\n<h3>P-de\u011feri Ne Anlama Gelir?<\/h3>\n\n\n\n<p>P-de\u011ferleri, verileriniz aras\u0131ndaki farklar\u0131n anlaml\u0131 olup olmad\u0131\u011f\u0131n\u0131 belirlemenize yard\u0131mc\u0131 olur. Ba\u015fka bir deyi\u015fle, g\u00f6zlemledi\u011finiz farkl\u0131l\u0131klar\u0131n rastgele \u015fans\u0131n sonucu olma olas\u0131l\u0131\u011f\u0131n\u0131n ne oldu\u011funu size s\u00f6yler.<\/p>\n\n\n\n<ul>\n<li>D\u00fc\u015f\u00fck p-de\u011feri (tipik olarak 0,05 veya daha d\u00fc\u015f\u00fck): Bu, fark\u0131n \u015fansa ba\u011fl\u0131 olma ihtimalinin d\u00fc\u015f\u00fck oldu\u011fu anlam\u0131na gelir. Yani, muhtemelen ger\u00e7ek bir fark vard\u0131r ve ilgin\u00e7 bir \u015feyler olmaktad\u0131r. Sonu\u00e7 olarak, hi\u00e7bir ili\u015fki olmad\u0131\u011f\u0131 fikrini (\"s\u0131f\u0131r hipotezi\") reddedersiniz.<\/li>\n<\/ul>\n\n\n\n<ul>\n<li>Y\u00fcksek p-de\u011feri (0,05'ten b\u00fcy\u00fck): Bu, fark\u0131n kolayca \u015fansa ba\u011fl\u0131 olabilece\u011fini g\u00f6sterir. Sonu\u00e7 olarak, verilerinizde ola\u011fand\u0131\u015f\u0131 bir \u015fey oldu\u011funa dair g\u00fc\u00e7l\u00fc bir g\u00f6sterge yoktur. Kategoriler aras\u0131nda bir ili\u015fki yoksa, s\u0131f\u0131r hipotezini reddetmezsiniz.<\/li>\n<\/ul>\n\n\n\n<h3>Sonu\u00e7lar Nas\u0131l \u00c7\u0131kar\u0131l\u0131r<\/h3>\n\n\n\n<p>Hem Ki-kare istatisti\u011fine hem de p-de\u011ferine sahip oldu\u011funuzda, sonu\u00e7lar \u00e7\u0131karabilirsiniz:<\/p>\n\n\n\n<p>P-de\u011ferine bak:<\/p>\n\n\n\n<ul>\n<li>E\u011fer p-de\u011feri 0,05 veya daha d\u00fc\u015f\u00fckse iki kategori aras\u0131nda bir ili\u015fki olmad\u0131\u011f\u0131 fikrini reddedersiniz. \u00d6rnek olarak, cinsiyetin \u00fcr\u00fcn tercihini etkileyip etkilemedi\u011fini incelerseniz ve p-de\u011feri d\u00fc\u015f\u00fckse (0,05 veya daha az), \u015f\u00f6yle diyebilirsiniz: \"G\u00f6r\u00fcn\u00fc\u015fe g\u00f6re cinsiyet insanlar\u0131n tercihlerini etkiliyor.\".<\/li>\n<\/ul>\n\n\n\n<ul>\n<li>E\u011fer p-de\u011feri 0,05'ten b\u00fcy\u00fckse, veriler anlaml\u0131 bir farkl\u0131l\u0131k g\u00f6stermez, dolay\u0131s\u0131yla kategorilerin muhtemelen ili\u015fkisiz oldu\u011fu sonucuna var\u0131rs\u0131n\u0131z. Y\u00fcksek bir p-de\u011feri (0,05'ten b\u00fcy\u00fck) kullanarak \u015f\u00f6yle diyebilirsiniz: \"Cinsiyetin \u00fcr\u00fcn tercihlerini etkiledi\u011fine dair g\u00fc\u00e7l\u00fc bir kan\u0131t yoktur.<\/li>\n<\/ul>\n\n\n\n<h3>Ger\u00e7ek d\u00fcnyayla ilgiyi unutmay\u0131n<\/h3>\n\n\n\n<p>\u0130statistiksel olarak anlaml\u0131 bir fark g\u00f6sterse bile, istatistiksel olarak anlaml\u0131 bir fark\u0131n ger\u00e7ek hayatta \u00f6nemli olup olmad\u0131\u011f\u0131n\u0131 d\u00fc\u015f\u00fcnmelisiniz. \u00c7ok b\u00fcy\u00fck bir veri setinde \u00e7ok k\u00fc\u00e7\u00fck farklar\u0131 bile \u00f6nemli g\u00f6rmek m\u00fcmk\u00fcnd\u00fcr, ancak ger\u00e7ek d\u00fcnyada \u00f6nemli bir etkisi olmayabilir. Sadece say\u0131lara bakmak yerine, her zaman sonucun pratikte ne anlama geldi\u011fini g\u00f6z \u00f6n\u00fcnde bulundurun.<\/p>\n\n\n\n<p>Ki-kare istatisti\u011fini kullanarak, bekledi\u011finiz ile elde etti\u011finiz aras\u0131ndaki fark\u0131n ger\u00e7ek mi yoksa sadece bir \u015fans m\u0131 oldu\u011funu s\u00f6yler. Verilerinizi birle\u015ftirdi\u011finizde anlaml\u0131 bir ili\u015fki olup olmad\u0131\u011f\u0131n\u0131 belirleyebilirsiniz.<\/p>\n\n\n\n<h2>Mind the Graph ile Ki-kare Test Sonu\u00e7lar\u0131n\u0131 G\u00f6rselle\u015ftirme<\/h2>\n\n\n\n<p>Ki-kare testi verilerdeki \u00f6r\u00fcnt\u00fclerin ortaya \u00e7\u0131kar\u0131lmas\u0131na yard\u0131mc\u0131 olur, ancak bu i\u00e7g\u00f6r\u00fclerin etkili bir \u015fekilde sunulmas\u0131 ilgi \u00e7ekici g\u00f6rseller gerektirir. <a href=\"https:\/\/mindthegraph.com\/science-figures\/?utm_source=blog&amp;utm_medium=cta-final&amp;utm_campaign=conversion\">Mind the Graph<\/a> ki-kare test sonu\u00e7lar\u0131n\u0131z i\u00e7in \u00e7arp\u0131c\u0131 g\u00f6rseller olu\u015fturmak i\u00e7in sezgisel ara\u00e7lar sa\u011flayarak karma\u015f\u0131k verilerin anla\u015f\u0131lmas\u0131n\u0131 kolayla\u015ft\u0131r\u0131r. \u0130ster akademik raporlar, sunumlar veya yay\u0131nlar i\u00e7in olsun, Mind the Graph istatistiksel i\u00e7g\u00f6r\u00fcleri netlik ve etki ile aktarman\u0131za yard\u0131mc\u0131 olur. Verilerinizi ilgi \u00e7ekici g\u00f6rsel hikayelere d\u00f6n\u00fc\u015ft\u00fcrmek i\u00e7in platformumuzu bug\u00fcn ke\u015ffedin.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img decoding=\"async\" loading=\"lazy\" src=\"https:\/\/mindthegraph.com\/blog\/wp-content\/uploads\/2023\/09\/mtg-80-plus-fields.gif\" alt=\"&quot;Biyoloji, kimya, fizik ve t\u0131p dahil olmak \u00fczere Mind the Graph&#039;de bulunan 80&#039;den fazla bilimsel alan\u0131 g\u00f6steren animasyonlu GIF, platformun ara\u015ft\u0131rmac\u0131lar i\u00e7in \u00e7ok y\u00f6nl\u00fcl\u00fc\u011f\u00fcn\u00fc g\u00f6stermektedir.&quot;\" class=\"wp-image-29586\" width=\"840\" height=\"555\"\/><figcaption class=\"wp-element-caption\">taraf\u0131ndan kapsanan \u00e7ok \u00e7e\u015fitli bilimsel alanlar\u0131 g\u00f6steren animasyonlu GIF <a href=\"https:\/\/mindthegraph.com\/science-figures\/?utm_source=blog&amp;utm_medium=cta-final&amp;utm_campaign=conversion\">Mind the Graph<\/a>.<\/figcaption><\/figure>\n\n\n\n<div class=\"is-content-justification-center is-layout-flex wp-container-1 wp-block-buttons\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link has-background wp-element-button\" href=\"https:\/\/mindthegraph.com\/science-figures\/?utm_source=blog&amp;utm_medium=cta-final&amp;utm_campaign=conversion\" style=\"background-color:#7833ff\"><strong>Mind the Graph ile G\u00fczel Grafikler Olu\u015fturun<\/strong><\/a><\/div>\n<\/div>\n\n\n\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>Kategorik verileri analiz etmek, hipotezleri test etmek ve de\u011fi\u015fkenler aras\u0131ndaki ili\u015fkileri ke\u015ffetmek i\u00e7in ki-kare testinin nas\u0131l kullan\u0131laca\u011f\u0131n\u0131 ke\u015ffedin.<\/p>","protected":false},"author":27,"featured_media":55804,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[961,977],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v19.9 - 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She is currently pursuing a master's degree in Bioentrepreneurship from Karolinska Institute. She is interested in health and diseases, global health, socioeconomic development, and women's health. 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