<\/p>\n
\u0130ki fakt\u00f6re b\u00f6l\u00fcnm\u00fc\u015f \u00fc\u00e7 veya daha fazla ba\u011f\u0131ms\u0131z grubun ortalamalar\u0131 aras\u0131nda istatistiksel olarak anlaml\u0131 bir fark olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in iki y\u00f6nl\u00fc ANOVA<\/a> kullan\u0131l\u0131r.<\/span><\/p>\n \u0130ki y\u00f6nl\u00fc ANOVA’n\u0131n amac\u0131, iki fakt\u00f6r\u00fcn bir yan\u0131t de\u011fi\u015fkeni \u00fczerindeki etkisini belirlemek ve iki fakt\u00f6r aras\u0131nda yan\u0131t de\u011fi\u015fkeni \u00fczerinde bir etkile\u015fim olup olmad\u0131\u011f\u0131n\u0131 belirlemektir.<\/span><\/p>\n Bu e\u011fitimde Python’da iki y\u00f6nl\u00fc ANOVA’n\u0131n nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r.<\/span><\/p>\n Bir botanik\u00e7i bitki b\u00fcy\u00fcmesinin g\u00fcne\u015f \u0131\u015f\u0131\u011f\u0131na maruz kalma ve sulama s\u0131kl\u0131\u011f\u0131ndan etkilenip etkilenmedi\u011fini bilmek ister. 30 tohum ekiyor ve iki ay boyunca farkl\u0131 g\u00fcne\u015f \u0131\u015f\u0131\u011f\u0131 ko\u015fullar\u0131nda ve sulama s\u0131kl\u0131\u011f\u0131nda b\u00fcy\u00fcmelerini sa\u011fl\u0131yor. \u0130ki ay sonra her bitkinin y\u00fcksekli\u011fini in\u00e7 cinsinden kaydediyor.<\/span><\/p>\n Sulama s\u0131kl\u0131\u011f\u0131 ve g\u00fcne\u015fe maruz kalman\u0131n bitki b\u00fcy\u00fcmesi \u00fczerinde \u00f6nemli bir etkiye sahip olup olmad\u0131\u011f\u0131n\u0131 belirlemek ve su s\u0131kl\u0131\u011f\u0131 ile g\u00fcne\u015fe maruz kalma aras\u0131nda bir etkile\u015fim etkisi olup olmad\u0131\u011f\u0131n\u0131 belirlemek amac\u0131yla iki y\u00f6nl\u00fc bir ANOVA ger\u00e7ekle\u015ftirmek i\u00e7in a\u015fa\u011f\u0131daki ad\u0131mlar\u0131 kullan\u0131n. sulama ve g\u00fcne\u015fe maruz kalma.<\/span><\/p>\n Ad\u0131m 1: Verileri girin.<\/strong><\/span><\/p>\n \u00d6ncelikle a\u015fa\u011f\u0131daki \u00fc\u00e7 de\u011fi\u015fkeni i\u00e7eren bir pandas DataFrame olu\u015fturaca\u011f\u0131z:<\/span><\/p>\n Ad\u0131m 2: \u0130ki y\u00f6nl\u00fc ANOVA’y\u0131 ger\u00e7ekle\u015ftirin.<\/strong><\/span><\/p>\n Daha sonra, statsmodels k\u00fct\u00fcphanesindeki anova_lm() fonksiyonunu<\/a> kullanarak iki y\u00f6nl\u00fc ANOVA’y\u0131 ger\u00e7ekle\u015ftirece\u011fiz:<\/span><\/p>\n Ad\u0131m 3: Sonu\u00e7lar\u0131 yorumlay\u0131n.<\/strong><\/span><\/p>\n Tablodaki fakt\u00f6rlerin her biri i\u00e7in a\u015fa\u011f\u0131daki p de\u011ferlerini g\u00f6rebiliriz:<\/span><\/p>\n Su ve g\u00fcne\u015f i\u00e7in p de\u011ferlerinin her ikisinin de 0,05’ten k\u00fc\u00e7\u00fck olmas\u0131, her iki fakt\u00f6r\u00fcn de bitki boyu \u00fczerinde istatistiksel olarak anlaml\u0131 bir etkiye sahip oldu\u011fu anlam\u0131na gelir.<\/span><\/p>\n Etkile\u015fim etkisinin p de\u011feri (0,120667) 0,05’ten az olmad\u0131\u011f\u0131ndan, bu bize g\u00fcne\u015fe maruz kalma ile sulama s\u0131kl\u0131\u011f\u0131 aras\u0131nda \u00f6nemli bir etkile\u015fim etkisinin olmad\u0131\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n Not:<\/strong> ANOVA sonu\u00e7lar\u0131 bize sulama s\u0131kl\u0131\u011f\u0131n\u0131n ve g\u00fcne\u015fe maruz kalman\u0131n bitki boyu \u00fczerinde istatistiksel olarak anlaml\u0131 bir etkiye sahip oldu\u011funu s\u00f6ylese de, Su ve g\u00fcne\u015f \u0131\u015f\u0131\u011f\u0131n\u0131n bitki boyunu nas\u0131l farkl\u0131 d\u00fczeylerde etkiledi\u011fini tam olarak belirlemek i\u00e7in post-hoc testler<\/a> yapmam\u0131z gerekecektir.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde Python’da di\u011fer genel g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Python’da Tek Y\u00f6nl\u00fc ANOVA Nas\u0131l Ger\u00e7ekle\u015ftirilir<\/a> \u0130ki fakt\u00f6re b\u00f6l\u00fcnm\u00fc\u015f \u00fc\u00e7 veya daha fazla ba\u011f\u0131ms\u0131z grubun ortalamalar\u0131 aras\u0131nda istatistiksel olarak anlaml\u0131 bir fark olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in iki y\u00f6nl\u00fc ANOVA kullan\u0131l\u0131r. \u0130ki y\u00f6nl\u00fc ANOVA’n\u0131n amac\u0131, iki fakt\u00f6r\u00fcn bir yan\u0131t de\u011fi\u015fkeni \u00fczerindeki etkisini belirlemek ve iki fakt\u00f6r aras\u0131nda yan\u0131t de\u011fi\u015fkeni \u00fczerinde bir etkile\u015fim olup olmad\u0131\u011f\u0131n\u0131 belirlemektir. Bu e\u011fitimde Python’da iki y\u00f6nl\u00fc ANOVA’n\u0131n nas\u0131l […]<\/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-855","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek: Python’da iki y\u00f6nl\u00fc ANOVA<\/strong><\/span><\/h2>\n
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import<\/span> numpy as<\/span> np\nimport<\/span> pandas as<\/span> pd\n\n#create data<\/span>\ndf = pd.DataFrame({'water': np.repeat(['daily', 'weekly'], 15),\n 'sun': np.tile(np.repeat(['low', 'med', 'high'], 5), 2),\n 'height': [6, 6, 6, 5, 6, 5, 5, 6, 4, 5,\n 6, 6, 7, 8, 7, 3, 4, 4, 4, 5,\n 4, 4, 4, 4, 4, 5, 6, 6, 7, 8]})\n\n#view first ten rows of data<\/span> \ndf[:10]\n\n\twater sun height\n0 daily low 6\n1 daily low 6\n2 daily low 6\n3 daily low 5\n4 daily low 6\n5 daily med 5\n6 daily med 5\n7 daily med 6\n8 daily med 4\n9 daily med 5\n<\/strong><\/pre>\n import<\/span> statsmodels.api as<\/span> sm\nfrom<\/span> statsmodels.formula.api import<\/span> ols\n\n#perform two-way ANOVA<\/span>\nmodel = ols('height ~ C(water) + C(sun) + C(water):C(sun)', data=df).fit()\nsm.stats.anova_lm(model, typ=2)\n\n\t sum_sq df F PR(>F)\nC(water) 8.533333 1.0 16.0000 0.000527\nC(sun) 24.866667 2.0 23.3125 0.000002\nC(water):C(sun) 2.466667 2.0 2.3125 0.120667\nResidual 12.800000 24.0 NaN NaN\n<\/strong><\/pre>\n\n
Ek kaynaklar<\/strong><\/span><\/h2>\n
Python’da \u00dc\u00e7 Yollu ANOVA Nas\u0131l Ger\u00e7ekle\u015ftirilir<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"