![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/hist_shape1.png\")
<\/p>\n
X ekseni veri k\u00fcmesinin de\u011ferlerini, Y ekseni ise her de\u011ferin s\u0131kl\u0131\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n Histogramlar faydal\u0131d\u0131r \u00e7\u00fcnk\u00fc bir veri k\u00fcmesindeki de\u011ferlerin da\u011f\u0131l\u0131m\u0131n\u0131 h\u0131zl\u0131 bir \u015fekilde anlamam\u0131za olanak tan\u0131rlar. Ayr\u0131ca iki farkl\u0131 veri k\u00fcmesini kar\u015f\u0131la\u015ft\u0131rmak i\u00e7in de kullan\u0131\u015fl\u0131d\u0131rlar.<\/span><\/p>\n \u0130ki veya daha fazla histogram\u0131 kar\u015f\u0131la\u015ft\u0131r\u0131rken \u00fc\u00e7 farkl\u0131 soruyu yan\u0131tlayabiliriz:<\/span><\/p>\n 1. Medyan de\u011ferler nas\u0131l kar\u015f\u0131la\u015ft\u0131r\u0131l\u0131r?<\/strong><\/span><\/p>\n Medyan\u0131n her histogram\u0131n ortas\u0131na yak\u0131n bir yerde oldu\u011funu kabaca tahmin edebiliriz, bu da da\u011f\u0131l\u0131mlar\u0131n medyan de\u011ferlerini kar\u015f\u0131la\u015ft\u0131rmam\u0131za olanak tan\u0131r.<\/span><\/p>\n 2. Da\u011f\u0131l\u0131m nas\u0131l kar\u015f\u0131la\u015ft\u0131r\u0131l\u0131r?<\/strong><\/span><\/p>\n Hangi histogram\u0131n daha yay\u0131lm\u0131\u015f oldu\u011funu g\u00f6rsel olarak g\u00f6rebiliyoruz, bu da bize hangi da\u011f\u0131l\u0131m\u0131n daha da\u011f\u0131n\u0131k de\u011ferlere sahip oldu\u011fu konusunda fikir veriyor.<\/span><\/p>\n 3. Asimetri nas\u0131l kar\u015f\u0131la\u015ft\u0131r\u0131l\u0131r?<\/strong><\/span><\/p>\n Bir histogram\u0131n grafi\u011fin sol taraf\u0131nda bir “kuyru\u011fu” varsa, bunun negatif \u00e7arp\u0131k oldu\u011fu s\u00f6ylenir. Tersine, e\u011fer bir histogram grafi\u011fin sa\u011f taraf\u0131nda bir “kuyru\u011fa” sahipse, bunun pozitif olarak \u00e7arp\u0131k oldu\u011fu s\u00f6ylenir. \u00c7arp\u0131kl\u0131\u011f\u0131<\/a> kar\u015f\u0131la\u015ft\u0131rmak i\u00e7in her histogram\u0131 g\u00f6rsel olarak kontrol edebiliriz.<\/span><\/p>\n A\u015fa\u011f\u0131daki \u00f6rnek, iki farkl\u0131 histogram\u0131n nas\u0131l kar\u015f\u0131la\u015ft\u0131r\u0131laca\u011f\u0131n\u0131 ve bu \u00fc\u00e7 sorunun nas\u0131l yan\u0131tlanaca\u011f\u0131n\u0131 g\u00f6sterir.<\/span><\/p>\n 200 \u00f6\u011frencinin bir s\u0131nava haz\u0131rlanmak i\u00e7in bir \u00e7al\u0131\u015fma y\u00f6ntemi kulland\u0131\u011f\u0131n\u0131 ve di\u011fer 200 \u00f6\u011frencinin de ayn\u0131 s\u0131nava haz\u0131rlanmak i\u00e7in farkl\u0131 bir \u00e7al\u0131\u015fma y\u00f6ntemi kulland\u0131\u011f\u0131n\u0131 varsayar\u0131z.<\/span><\/p>\n Her \u00f6\u011frenci grubunun s\u0131nav sonu\u00e7lar\u0131n\u0131 kar\u015f\u0131la\u015ft\u0131rmak i\u00e7in a\u015fa\u011f\u0131daki histogramlar\u0131 olu\u015fturdu\u011fumuzu varsayal\u0131m:<\/span> <\/p>\n Bu histogramlar\u0131 kar\u015f\u0131la\u015ft\u0131rabilir ve a\u015fa\u011f\u0131daki \u00fc\u00e7 soruyu yan\u0131tlayabiliriz:<\/span><\/p>\n 1. Medyan de\u011ferler nas\u0131l kar\u015f\u0131la\u015ft\u0131r\u0131l\u0131r?<\/strong><\/span><\/p>\n Basit\u00e7e histogramlara bakarak her da\u011f\u0131l\u0131m\u0131n tam ortanca de\u011ferini bilemesek de, Y\u00f6ntem 1’i kullanan \u00f6\u011frencilerin ortanca s\u0131nav puan\u0131n\u0131n, Y\u00f6ntem 1’i kullanan \u00f6\u011frencilerin ortanca s\u0131nav puan\u0131ndan daha y\u00fcksek oldu\u011fu a\u00e7\u0131kt\u0131r. y\u00f6ntem 2.<\/span><\/p>\n Y\u00f6ntem 1’in medyan de\u011ferinin 84 civar\u0131nda, y\u00f6ntem 2’nin medyan de\u011ferinin ise 78 civar\u0131nda oldu\u011funu tahmin edebiliriz.<\/span><\/p>\n 2. Da\u011f\u0131l\u0131m nas\u0131l kar\u015f\u0131la\u015ft\u0131r\u0131l\u0131r?<\/strong><\/span><\/p>\n Y\u00f6ntem 2’ye ait histogram de\u011ferleri, Y\u00f6ntem 1’e g\u00f6re \u00e7ok daha da\u011f\u0131n\u0131kt\u0131r; bu da bize, Y\u00f6ntem 2’yi kullanan \u00f6\u011frencilerin s\u0131nav sonu\u00e7lar\u0131nda \u00e7ok daha b\u00fcy\u00fck bir da\u011f\u0131l\u0131m oldu\u011funu g\u00f6sterir.<\/span><\/p>\n 3. Asimetri nas\u0131l kar\u015f\u0131la\u015ft\u0131r\u0131l\u0131r?<\/strong><\/span><\/p>\n Histogramlara bak\u0131ld\u0131\u011f\u0131nda, Y\u00f6ntem 1 i\u00e7in test puanlar\u0131n\u0131n da\u011f\u0131l\u0131m\u0131n\u0131n, histogram\u0131n sa\u011f\u0131na do\u011fru uzanan “kuyruk” ile g\u00f6sterildi\u011fi gibi, hafif\u00e7e sa\u011fa \u00e7arp\u0131k oldu\u011fu g\u00f6r\u00fclmektedir.<\/span><\/p>\n Ancak 2. y\u00f6nteme ili\u015fkin s\u0131nav sonu\u00e7lar\u0131n\u0131n da\u011f\u0131l\u0131m\u0131nda bir \u201ckuyruk\u201d g\u00f6r\u00fcnm\u00fcyor, bu da bize da\u011f\u0131l\u0131m\u0131n \u00e7ok az veya \u00e7arp\u0131k olmad\u0131\u011f\u0131n\u0131 g\u00f6steriyor.<\/span><\/p>\n Bonus<\/strong> : \u0130\u015fte bu iki histogram\u0131 olu\u015fturmak i\u00e7in R’de kulland\u0131\u011f\u0131m\u0131z kod:<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde histogramlarla di\u011fer ortak g\u00f6revlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/p>\n Herhangi bir histogram\u0131n ortalamas\u0131 ve medyan\u0131 nas\u0131l tahmin edilir?<\/a> Histogram, bir veri k\u00fcmesindeki de\u011ferlerin da\u011f\u0131l\u0131m\u0131n\u0131 g\u00f6rselle\u015ftirmemize olanak tan\u0131yan bir grafik t\u00fcr\u00fcd\u00fcr. X ekseni veri k\u00fcmesinin de\u011ferlerini, Y ekseni ise her de\u011ferin s\u0131kl\u0131\u011f\u0131n\u0131 g\u00f6sterir. Histogramlar faydal\u0131d\u0131r \u00e7\u00fcnk\u00fc bir veri k\u00fcmesindeki de\u011ferlerin da\u011f\u0131l\u0131m\u0131n\u0131 h\u0131zl\u0131 bir \u015fekilde anlamam\u0131za olanak tan\u0131rlar. Ayr\u0131ca iki farkl\u0131 veri k\u00fcmesini kar\u015f\u0131la\u015ft\u0131rmak i\u00e7in de kullan\u0131\u015fl\u0131d\u0131rlar. \u0130ki veya daha fazla histogram\u0131 kar\u015f\u0131la\u015ft\u0131r\u0131rken \u00fc\u00e7 farkl\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-3612","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n \u00d6rnek: histogramlar\u0131 kar\u015f\u0131la\u015ft\u0131rma<\/strong><\/span><\/h2>\n
![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/comparerhistogrammes2.jpg\")
<\/p>\n library<\/span> (ggplot2)\n\n#make this example reproducible\n<\/span>set. seeds<\/span> (0)\n\n#create data frame\n<\/span>df <- data. frame<\/span> (method=rep(c(' Method 1<\/span> ', ' Method 2<\/span> '), each= 200<\/span> ),\n Score=c(rnorm( 200<\/span> , mean= 84<\/span> , sd= 2<\/span> ),\n rnorm( 200<\/span> , mean= 78<\/span> , sd= 4<\/span> )))\n\n#create histogram of scores for each method\n<\/span>ggplot(df, aes(x=Score)) +\n geom_histogram(fill=' steelblue<\/span> ', color=' black<\/span> ') +\n facet_wrap(.~method, nrow= 2<\/span> ) +\n labs(title=' Exam Scores by Study Method<\/span> ')\n<\/strong><\/span><\/pre>\n Ek kaynaklar<\/strong><\/span><\/h2>\n
Herhangi bir histogram\u0131n standart sapmas\u0131 nas\u0131l tahmin edilir?<\/a>
Histogramlar\u0131n \u015fekli nas\u0131l tan\u0131mlan\u0131r?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"