\u00d6rne\u011fin, a\u015fa\u011f\u0131daki s\u0131f\u0131r ve alternatif hipotezlere sahip oldu\u011fumuzu varsayal\u0131m:<\/span><\/p>\n H 0<\/sub> :<\/strong> \u03bc 1<\/sub> = \u03bc 2<\/sub> = \u03bc 3<\/sub> = \u2026 = \u03bc k<\/sub> (t\u00fcm pop\u00fclasyon ortalamalar\u0131 e\u015fittir)<\/span><\/p>\n H A<\/sub> :<\/strong> En az bir n\u00fcfus ortalamas\u0131 di\u011ferlerinden farkl\u0131<\/span><\/p>\n Bu bir \u00e7ok ama\u00e7l\u0131 test \u00f6rne\u011fidir \u00e7\u00fcnk\u00fc s\u0131f\u0131r hipotezi ikiden fazla parametre i\u00e7erir.<\/span><\/p>\n S\u0131f\u0131r hipotezini reddedersek, en az bir pop\u00fclasyon ortalamas\u0131n\u0131n di\u011ferlerinden farkl\u0131 oldu\u011funu biliyoruz, ancak hangi pop\u00fclasyon ortalamas\u0131n\u0131n farkl\u0131 oldu\u011funu spesifik olarak bilmiyoruz.<\/span><\/p>\n Omnibus testi \u00e7o\u011funlukla ANOVA modellerinde<\/a> ve \u00e7oklu do\u011frusal regresyon modellerinde<\/a> g\u00f6r\u00fcl\u00fcr.<\/span><\/p>\n Bu e\u011fitimde, tek y\u00f6nl\u00fc ANOVA ve \u00e7oklu do\u011frusal regresyon modelinde \u00e7ok ama\u00e7l\u0131 testin bir \u00f6rne\u011fi sunulmaktad\u0131r.<\/span><\/p>\n Bir profes\u00f6r\u00fcn \u00fc\u00e7 farkl\u0131 s\u0131nava haz\u0131rl\u0131k program\u0131n\u0131n farkl\u0131 s\u0131nav puanlar\u0131na yol a\u00e7\u0131p a\u00e7mad\u0131\u011f\u0131n\u0131 bilmek istedi\u011fini varsayal\u0131m. Bunu test etmek i\u00e7in, bir ay boyunca her test haz\u0131rl\u0131k program\u0131n\u0131 kullanmak \u00fczere 10 \u00f6\u011frenciyi rastgele g\u00f6revlendiriyor ve ard\u0131ndan her gruptaki \u00f6\u011frencilere ayn\u0131 s\u0131nav\u0131 uyguluyor.<\/span><\/p>\n Her gruba ait s\u0131nav sonu\u00e7lar\u0131 a\u015fa\u011f\u0131da g\u00f6sterilmektedir:<\/span> <\/p>\n Her haz\u0131rl\u0131k program\u0131n\u0131n ayn\u0131 s\u0131nav sonu\u00e7lar\u0131na yol a\u00e7\u0131p a\u00e7mad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in a\u015fa\u011f\u0131daki bo\u015f ve alternatif hipotezleri kullanarak tek y\u00f6nl\u00fc bir ANOVA ger\u00e7ekle\u015ftirir:<\/span><\/p>\n H 0<\/sub> :<\/strong> \u00b5 1<\/sub> = \u00b5 2<\/sub> = \u00b5 3<\/sub><\/span><\/p>\n H A<\/sub> :<\/strong> En az bir s\u0131nava haz\u0131rl\u0131k program\u0131 di\u011ferlerinden farkl\u0131 ortalama notlara yol a\u00e7maktad\u0131r.<\/span><\/p>\n Bu bir \u00e7ok ama\u00e7l\u0131 test \u00f6rne\u011fidir \u00e7\u00fcnk\u00fc s\u0131f\u0131r hipotezinin ikiden fazla parametresi vard\u0131r.<\/span><\/p>\n Tek y\u00f6nl\u00fc bir ANOVA hesaplay\u0131c\u0131<\/a> kullanarak a\u015fa\u011f\u0131daki ANOVA tablosunu \u00fcretebilir:<\/span> <\/p>\n S\u0131f\u0131r hipotezini reddedip reddedemeyece\u011fini belirlemek i\u00e7in F testi istatisti\u011fine ve tablodaki kar\u015f\u0131l\u0131k gelen p de\u011ferine bakmas\u0131 yeterlidir.<\/span><\/p>\n F testi istatisti\u011fi 2,358’dir<\/strong> ve kar\u015f\u0131l\u0131k gelen p de\u011feri 0,11385’tir<\/strong> . Bu p de\u011feri 0,05’ten k\u00fc\u00e7\u00fck olmad\u0131\u011f\u0131 i\u00e7in s\u0131f\u0131r hipotezini reddetmemektedir.<\/span><\/p>\n Ba\u015fka bir deyi\u015fle, s\u0131nav haz\u0131rl\u0131k programlar\u0131ndan herhangi birinin farkl\u0131 ortalama s\u0131nav puanlar\u0131na yol a\u00e7t\u0131\u011f\u0131n\u0131 s\u00f6ylemek i\u00e7in yeterli kan\u0131t yoktur.<\/span><\/p>\n Not:<\/strong> E\u011fer p de\u011feri 0,05’ten k\u00fc\u00e7\u00fck olsayd\u0131 profes\u00f6r s\u0131f\u0131r hipotezini reddederdi. Daha sonra hangi programlar\u0131n farkl\u0131 ortalama s\u0131nav puanlar\u0131 \u00fcretti\u011fini tam olarak belirlemek i\u00e7in post-hoc testler<\/a> ger\u00e7ekle\u015ftirebilir.<\/span><\/p>\n Bir profes\u00f6r\u00fcn, \u00e7al\u0131\u015f\u0131lan saatlerin ve al\u0131nan uygulama s\u0131navlar\u0131n\u0131n say\u0131s\u0131n\u0131n, bir \u00f6\u011frencinin s\u0131navda alaca\u011f\u0131 notu tahmin edip edemeyece\u011fini belirlemek istedi\u011fini varsayal\u0131m.<\/span><\/p>\n Bunu test etmek i\u00e7in 20 \u00f6\u011frenciden veri topluyor ve a\u015fa\u011f\u0131daki \u00e7oklu do\u011frusal regresyon modeline uyuyor:<\/span><\/p>\n S\u0131nav puan\u0131 = \u03b2 0<\/sub> + \u03b2 1<\/sub> (saat) + \u03b2 2<\/sub> (haz\u0131rl\u0131k s\u0131navlar\u0131)<\/span><\/p>\n Bu regresyon modeli a\u015fa\u011f\u0131daki bo\u015f ve alternatif hipotezleri kullan\u0131r:<\/span><\/p>\n H 0<\/sub> :<\/strong> \u03b2 1<\/sub> = \u03b2 2<\/sub> = 0<\/span><\/p>\n H A<\/sub> :<\/strong> En az bir katsay\u0131 s\u0131f\u0131ra e\u015fit de\u011fildir.<\/span><\/p>\n Bu \u00e7ok ama\u00e7l\u0131 testin bir \u00f6rne\u011fidir \u00e7\u00fcnk\u00fc s\u0131f\u0131r hipotezi ayn\u0131 anda birden fazla parametrenin s\u0131f\u0131ra e\u015fit olup olmad\u0131\u011f\u0131n\u0131 test eder.<\/span><\/p>\n Excel’deki a\u015fa\u011f\u0131daki regresyon \u00e7\u0131kt\u0131s\u0131<\/a> bu regresyon modelinin sonu\u00e7lar\u0131n\u0131 g\u00f6sterir:<\/span> <\/p>\n S\u0131f\u0131r hipotezini reddedip reddedemeyece\u011fini belirlemek i\u00e7in F testi istatisti\u011fine ve tablodaki kar\u015f\u0131l\u0131k gelen p de\u011ferine bakmas\u0131 yeterlidir.<\/span><\/p>\n F testi istatisti\u011fi 23,46’d\u0131r<\/strong> ve buna kar\u015f\u0131l\u0131k gelen p de\u011feri 0,00’d\u0131r<\/strong> . Bu p de\u011feri 0,05’ten k\u00fc\u00e7\u00fck oldu\u011fundan s\u0131f\u0131r hipotezi reddedilebilir ve modeldeki katsay\u0131lardan en az birinin s\u0131f\u0131ra e\u015fit olmad\u0131\u011f\u0131 sonucuna var\u0131labilir.<\/span><\/p>\n Ancak bu \u00e7ok ama\u00e7l\u0131 testin s\u0131f\u0131r hipotezini basit\u00e7e reddetmek, asl\u0131nda modeldeki hangi katsay\u0131lar\u0131n s\u0131f\u0131ra e\u015fit olmad\u0131\u011f\u0131n\u0131 s\u00f6ylemez. Bunu belirlemek i\u00e7in modeldeki bireysel katsay\u0131lar\u0131n p de\u011ferlerine bakmas\u0131 gerekir:<\/span><\/p>\n Bu ona saatlerin s\u0131nav notunun istatistiksel olarak anlaml\u0131 bir belirleyicisi oldu\u011funu, ancak deneme s\u0131navlar\u0131n\u0131n \u00f6yle olmad\u0131\u011f\u0131n\u0131 s\u00f6yl\u00fcyor.<\/span><\/p>\n \u0130\u015fte bu makalede \u00f6\u011frendiklerimizin bir \u00f6zeti:<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde Excel’de tek y\u00f6nl\u00fc ANOVA ve \u00e7oklu do\u011frusal regresyonun nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Excel’de Tek Y\u00f6nl\u00fc ANOVA Nas\u0131l Ger\u00e7ekle\u015ftirilir<\/a> \u0130statistikte \u00e7ok ama\u00e7l\u0131 test , bir modelin \u00e7e\u015fitli parametrelerinin \u00f6nemini ayn\u0131 anda test eden herhangi bir istatistiksel testtir. \u00d6rne\u011fin, a\u015fa\u011f\u0131daki s\u0131f\u0131r ve alternatif hipotezlere sahip oldu\u011fumuzu varsayal\u0131m: H 0 : \u03bc 1 = \u03bc 2 = \u03bc 3 = \u2026 = \u03bc k (t\u00fcm pop\u00fclasyon ortalamalar\u0131 e\u015fittir) H A : En az bir n\u00fcfus ortalamas\u0131 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-1525","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n Tek y\u00f6nl\u00fc ANOVA’da \u00e7ok ama\u00e7l\u0131 test<\/strong><\/span><\/h3>\n
![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/aller-simple2.png\")
<\/p>\n![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/oneway4.png\")
<\/p>\n \u00c7oklu do\u011frusal regresyon modelinde \u00e7ok ama\u00e7l\u0131 test<\/strong><\/span><\/h3>\n
![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/multipleregexcel4.png\")
<\/p>\n\n
\u00d6zet<\/strong><\/span><\/h2>\n
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Ek kaynaklar<\/strong><\/span><\/h2>\n
Excel’de \u00e7oklu do\u011frusal regresyon nas\u0131l ger\u00e7ekle\u015ftirilir<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"