{"id":482,"date":"2023-07-29T18:17:31","date_gmt":"2023-07-29T18:17:31","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d8%a7%d9%94%d9%86%d9%83%d9%88%d9%81%d8%a7-%d9%81%d9%8a-%d8%b5\/"},"modified":"2023-07-29T18:17:31","modified_gmt":"2023-07-29T18:17:31","slug":"%d8%a7%d9%94%d9%86%d9%83%d9%88%d9%81%d8%a7-%d9%81%d9%8a-%d8%b5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/%d8%a7%d9%94%d9%86%d9%83%d9%88%d9%81%d8%a7-%d9%81%d9%8a-%d8%b5\/","title":{"rendered":"\u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ancova) \u0641\u064a r"},"content":{"rendered":"

<\/p>\n

\n

\u064a\u0642\u062f\u0645 \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0645\u062b\u0627\u0644\u0627\u064b \u0644\u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA)<\/a> \u0641\u064a R.<\/span><\/p>\n

\u0645\u062b\u0627\u0644: \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0641\u064a R<\/strong><\/span><\/h3>\n

\u0633\u0646\u0642\u0648\u0645 \u0628\u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0644\u0627\u062e\u062a\u0628\u0627\u0631 \u0645\u0627 \u0625\u0630\u0627 \u0643\u0627\u0646 \u0623\u0633\u0644\u0648\u0628 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0644\u0647 \u062a\u0623\u062b\u064a\u0631 \u0639\u0644\u0649 \u0646\u062a\u0627\u0626\u062c \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646 \u0623\u0645 \u0644\u0627 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0627\u0644\u062a\u0627\u0644\u064a\u0629:<\/span><\/p>\n

    \n
  • \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0627\u0644\u0641\u0646\u064a\u0629<\/strong> : \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0645\u0633\u062a\u0642\u0644 \u0627\u0644\u0630\u064a \u0646\u0631\u063a\u0628 \u0641\u064a \u062a\u062d\u0644\u064a\u0644\u0647<\/span><\/li>\n
  • \u062f\u0631\u062c\u0629 \u0627\u0644\u0637\u0627\u0644\u0628 \u0627\u0644\u062d\u0627\u0644\u064a\u0629<\/strong> : \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0645\u0634\u062a\u0631\u0643 \u0627\u0644\u0630\u064a \u0646\u0631\u063a\u0628 \u0641\u064a \u0623\u062e\u0630\u0647 \u0628\u0639\u064a\u0646 \u0627\u0644\u0627\u0639\u062a\u0628\u0627\u0631<\/span><\/li>\n
  • \u0646\u0642\u0627\u0637 \u0627\u0644\u0645\u0631\u0627\u062c\u0639\u0629<\/strong> : \u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0627\u0644\u0627\u0633\u062a\u062c\u0627\u0628\u0629 \u0627\u0644\u062a\u064a \u0646\u0631\u064a\u062f \u062a\u062d\u0644\u064a\u0644\u0647\u0627<\/span><\/li>\n<\/ul>\n

    \u062a\u062d\u062a\u0648\u064a \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0639\u0644\u0649 \u0645\u0639\u0644\u0648\u0645\u0627\u062a \u0639\u0646 90 \u0637\u0627\u0644\u0628\u064b\u0627 \u0645\u0642\u0633\u0645\u064a\u0646 \u0639\u0634\u0648\u0627\u0626\u064a\u064b\u0627 \u0625\u0644\u0649 \u062b\u0644\u0627\u062b \u0645\u062c\u0645\u0648\u0639\u0627\u062a \u0645\u0643\u0648\u0646\u0629 \u0645\u0646 30 \u0637\u0627\u0644\u0628\u064b\u0627.<\/span><\/p>\n

    \u062a\u0639\u0631\u0636 \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0623\u0633\u0644\u0648\u0628 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0627\u0644\u0630\u064a \u0627\u0633\u062a\u062e\u062f\u0645\u0647 \u0643\u0644 \u0637\u0627\u0644\u0628 (\u0623\u060c \u0628<\/em> \u060c \u0623\u0648 \u062c)<\/em> \u060c<\/em> \u0648\u062f\u0631\u062c\u062a\u0647 \u0627\u0644\u062d\u0627\u0644\u064a\u0629 \u0641\u064a \u0627\u0644\u0641\u0635\u0644 \u0639\u0646\u062f\u0645\u0627 \u0628\u062f\u0623 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0623\u0633\u0644\u0648\u0628 \u0627\u0644\u062f\u0631\u0627\u0633\u0629\u060c \u0648\u0627\u0644\u062f\u0631\u062c\u0629 \u0627\u0644\u062a\u064a \u062d\u0635\u0644 \u0639\u0644\u064a\u0647\u0627 \u0641\u064a \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646 \u0628\u0639\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0623\u0633\u0644\u0648\u0628 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0644\u0645\u062f\u0629 \u0634\u0647\u0631 \u0644\u0644\u062a\u062d\u0636\u064a\u0631 \u0644\u0644\u0627\u0645\u062a\u062d\u0627\u0646. \u0627\u0645\u062a\u062d\u0627\u0646:<\/span><\/p>\n

     #make this example reproducible<\/span>\nset.seed(10)\n\n#create dataset<\/span>\ndata <- data.frame(technique = rep(c(\"A\", \"B\", \"C\"), each = 30),\n                   current_grade = runif(90, 65, 95),\n                   exam = c(runif(30, 80, 95), runif(30, 70, 95), runif(30, 70, 90)))\n\n#view first six lines of dataset<\/span>\nhead(data)\n\n# technical current_grade exam\n#1 A 80.22435 87.32759\n#2 A 74.20306 90.67114\n#3 A 77.80723 88.87902\n#4 A 85.79306 87.75735\n#5 A 67.55408 85.72442\n#6 A 71.76310 92.52167\n<\/strong><\/pre>\n
     \u0627\u0644\u062e\u0637\u0648\u0629 1: \u0627\u0633\u062a\u0643\u0634\u0627\u0641 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a<\/strong><\/span><\/h3>\n
     \u0642\u0628\u0644 \u0645\u0644\u0627\u0621\u0645\u0629 \u0646\u0645\u0648\u0630\u062c \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA)\u060c \u0646\u062d\u062a\u0627\u062c \u0623\u0648\u0644\u0627\u064b \u0625\u0644\u0649 \u0627\u0633\u062a\u0643\u0634\u0627\u0641 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0644\u0641\u0647\u0645\u0647\u0627 \u0628\u0634\u0643\u0644 \u0623\u0641\u0636\u0644 \u0648\u0627\u0644\u062a\u062d\u0642\u0642 \u0645\u0646 \u0639\u062f\u0645 \u0648\u062c\u0648\u062f \u0642\u064a\u0645 \u0645\u062a\u0637\u0631\u0641\u0629 \u064a\u0645\u0643\u0646 \u0623\u0646 \u062a\u0624\u062f\u064a \u0625\u0644\u0649 \u062a\u062d\u0631\u064a\u0641 \u0627\u0644\u0646\u062a\u0627\u0626\u062c.<\/span><\/p>\n
     \u0623\u0648\u0644\u0627\u064b\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0639\u0631\u0636 \u0645\u0644\u062e\u0635 \u0644\u0643\u0644 \u0645\u062a\u063a\u064a\u0631 \u0641\u064a \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a:<\/span><\/p>\n
     summary(data)\n\n# technical current_grade exam      \n#A:30 Min. :65.43 Min. :71.17  \n# B:30 1st Qu.:71.79 1st Qu.:77.27  \n# C:30 Median:77.84 Median:84.69  \n# Mean:78.15 Mean:83.38  \n# 3rd Qu.:83.65 3rd Qu.:89.22  \n# Max. :93.84 Max. :94.76  \n<\/strong><\/pre>\n
     \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646 \u0643\u0644 \u0642\u064a\u0645\u0629 \u062a\u0642\u0646\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 ( \u0623\u060c \u0628<\/em> \u060c \u062c)<\/em> \u062a\u0638\u0647\u0631 30 \u0645\u0631\u0629 \u0641\u064a \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a.<\/span><\/p>\n
     \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u064a\u0636\u064b\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0643\u064a\u0641 \u062a\u0645 \u062a\u0648\u0632\u064a\u0639 \u062f\u0631\u062c\u0627\u062a \u0627\u0644\u0637\u0644\u0627\u0628 \u0627\u0644\u062d\u0627\u0644\u064a\u0629 \u0641\u064a \u0628\u062f\u0627\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629. \u0648\u0643\u0627\u0646 \u0627\u0644\u062d\u062f \u0627\u0644\u0623\u062f\u0646\u0649 \u0644\u0644\u062f\u0631\u062c\u0627\u062a \u0641\u064a \u0627\u0644\u0641\u0635\u0644 65.43\u060c \u0648\u0627\u0644\u062d\u062f \u0627\u0644\u0623\u0642\u0635\u0649 93.84\u060c \u0648\u0627\u0644\u0645\u0639\u062f\u0644 78.15.<\/span><\/p>\n
     \u0648\u0628\u0627\u0644\u0645\u062b\u0644\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646 \u0627\u0644\u062d\u062f \u0627\u0644\u0623\u062f\u0646\u0649 \u0645\u0646 \u0627\u0644\u062f\u0631\u062c\u0627\u062a \u0627\u0644\u062a\u064a \u062a\u0645 \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u064a\u0647\u0627 \u0641\u064a \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646 \u0643\u0627\u0646 71.17\u060c \u0648\u0643\u0627\u0646 \u0627\u0644\u062d\u062f \u0627\u0644\u0623\u0642\u0635\u0649 \u0644\u0644\u062f\u0631\u062c\u0627\u062a 94.76 \u0648\u0643\u0627\u0646 \u0627\u0644\u0645\u062a\u0648\u0633\u0637 83.38.<\/span><\/p>\n
     \u062b\u0645 \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u062d\u0632\u0645\u0629 dplyr<\/strong> \u0644\u0644\u0639\u062b\u0648\u0631 \u0628\u0633\u0647\u0648\u0644\u0629 \u0639\u0644\u0649 \u0627\u0644\u0645\u062a\u0648\u0633\u0637 \u0648\u0627\u0644\u0627\u0646\u062d\u0631\u0627\u0641 \u0627\u0644\u0645\u0639\u064a\u0627\u0631\u064a \u0644\u0644\u062f\u0631\u062c\u0627\u062a \u0627\u0644\u062d\u0627\u0644\u064a\u0629 \u0648\u0646\u062a\u0627\u0626\u062c \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646\u0627\u062a \u0644\u0643\u0644 \u0623\u0633\u0644\u0648\u0628 \u062f\u0631\u0627\u0633\u0629:<\/span><\/p>\n
     #load dplyr<\/em><\/span>\nlibrary(dplyr)\n\ndata %>%\n  group_by<\/span> (technical) %>%\n  summarize<\/span> (mean_grade = mean(current_grade),\n            sd_grade = sd(current_grade),\n            mean_exam = mean(exam),\n            sd_exam = sd(exam))\n\n# A tibble: 3 x 5\n# technique mean_grade sd_grade mean_exam sd_exam                      \n#1 A 79.0 7.00 88.5 3.88\n#2 B 78.5 8.33 81.8 7.62\n#3 C 76.9 8.24 79.9 5.71<\/strong><\/pre>\n
     \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646 \u0627\u0644\u0645\u062a\u0648\u0633\u0637\u0627\u062a \u0648\u0627\u0644\u0627\u0646\u062d\u0631\u0627\u0641\u0627\u062a \u0627\u0644\u0645\u0639\u064a\u0627\u0631\u064a\u0629 \u0644\u0644\u0635\u0641 \u0627\u0644\u062d\u0627\u0644\u064a \u0644\u0644\u0637\u0644\u0627\u0628 \u0627\u0644\u0630\u064a\u0646 \u064a\u0633\u062a\u062e\u062f\u0645\u0648\u0646 \u0643\u0644 \u0623\u0633\u0644\u0648\u0628 \u0645\u0646 \u0623\u0633\u0627\u0644\u064a\u0628 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0645\u062a\u0634\u0627\u0628\u0647\u0629 \u062a\u0642\u0631\u064a\u0628\u064b\u0627.<\/span><\/p>\n
     \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u064a\u0636\u064b\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646 \u0645\u062a\u0648\u0633\u0637 \u062f\u0631\u062c\u0627\u062a \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646 \u0623\u0639\u0644\u0649 \u0628\u0643\u062b\u064a\u0631 \u0644\u0644\u0637\u0644\u0627\u0628 \u0627\u0644\u0630\u064a\u0646 \u0627\u0633\u062a\u062e\u062f\u0645\u0648\u0627 \u0623\u0633\u0644\u0648\u0628 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 (\u0623)<\/em> \u0645\u0642\u0627\u0631\u0646\u0629\u064b \u0628\u0627\u0644\u062a\u0642\u0646\u064a\u0627\u062a (\u0628)<\/em> \u0648 (\u062c)<\/em> .<\/span><\/p>\n
     \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u064a\u0636\u064b\u0627 \u062a\u0635\u0648\u0631 \u062a\u0648\u0632\u064a\u0639 \u0646\u062a\u0627\u0626\u062c \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646\u0627\u062a \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u062a\u0642\u0646\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 boxplots :<\/span><\/p>\n
     boxplot(exam ~ technique,\ndata = data,\nmain = \"Exam Score by Studying Technique\",\nxlab = \"Studying Technique\",\nylab = \"Exam Score\",\ncol = \"steelblue\",\nborder = \"black\"\n)<\/strong><\/pre>\n
    <\/h3>\n
     \u0648\u0628\u0627\u0644\u0645\u062b\u0644\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u064a\u0636\u064b\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 boxplots \u0644\u062a\u0635\u0648\u0631 \u062a\u0648\u0632\u064a\u0639 \u0627\u0644\u062f\u0631\u062c\u0627\u062a \u0627\u0644\u062d\u0627\u0644\u064a\u0629<\/em> \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u062a\u0642\u0646\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629:<\/span><\/p>\n
     boxplot(current_grade ~ technical,\ndata = data,\nmain = \"Current Grade by Studying Technique\",\nxlab = \"Studying Technique\",\nylab = \"Current Grade\",\ncol = \"steelblue\",\nborder = \"black\"\n)<\/strong><\/pre>\n
     \u0627\u0644\u062e\u0637\u0648\u0629 2: \u0627\u0644\u062a\u062d\u0642\u0642 \u0645\u0646 \u0627\u0641\u062a\u0631\u0627\u0636\u0627\u062a \u0627\u0644\u0646\u0645\u0648\u0630\u062c<\/strong><\/span><\/h3>\n
     \u0628\u0645\u062c\u0631\u062f \u0642\u064a\u0627\u0645\u0646\u0627 \u0628\u0628\u0639\u0636 \u0627\u0633\u062a\u0643\u0634\u0627\u0641 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0623\u0633\u0627\u0633\u064a\u0629 \u0648\u0627\u0644\u062a\u0639\u0631\u0641 \u0639\u0644\u0649 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a\u060c \u0646\u062d\u062a\u0627\u062c \u0625\u0644\u0649 \u0627\u0644\u062a\u062d\u0642\u0642 \u0645\u0646 \u0627\u0633\u062a\u064a\u0641\u0627\u0621 \u0627\u0644\u0627\u0641\u062a\u0631\u0627\u0636\u0627\u062a \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0644\u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA):<\/span><\/p>\n
      \n
    •  \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0645\u0634\u062a\u0631\u0643 \u0648\u0627\u0644\u0645\u0639\u0627\u0645\u0644\u0629 \u0645\u0633\u062a\u0642\u0644\u0627\u0646<\/strong> \u2013 \u0645\u0646 \u0627\u0644\u0636\u0631\u0648\u0631\u064a \u0627\u0644\u062a\u062d\u0642\u0642 \u0645\u0646 \u0623\u0646 \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0645\u0634\u062a\u0631\u0643 ( \u0627\u0644\u0635\u0641 \u0627\u0644\u062d\u0627\u0644\u064a)<\/em> \u0648\u0627\u0644\u0645\u0639\u0627\u0645\u0644\u0629 (\u062a\u0642\u0646\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629)<\/em> \u0645\u0633\u062a\u0642\u0644\u0627\u0646 \u0639\u0646 \u0628\u0639\u0636\u0647\u0645\u0627 \u0627\u0644\u0628\u0639\u0636\u060c \u0644\u0623\u0646 \u0625\u0636\u0627\u0641\u0629 \u0645\u0635\u0637\u0644\u062d \u0645\u062a\u063a\u064a\u0631 \u0641\u064a \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u064a\u0643\u0648\u0646 \u0630\u0627 \u0645\u0639\u0646\u0649 \u0641\u0642\u0637 \u0625\u0630\u0627 \u0643\u0627\u0646 \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0645\u0634\u062a\u0631\u0643 \u0648\u0627\u0644\u0645\u0639\u0627\u0645\u0644\u0629 \u0645\u0633\u062a\u0642\u0644\u064a\u0646 \u0639\u0646 \u0628\u0639\u0636\u0647\u0645\u0627 \u0627\u0644\u0628\u0639\u0636 \u0627\u0644\u0639\u0644\u0627\u062c \u064a\u0639\u0645\u0644 \u0628\u0634\u0643\u0644 \u0645\u0633\u062a\u0642\u0644 \u0639\u0644\u0649 \u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0627\u0633\u062a\u062c\u0627\u0628\u0629 ( \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646<\/em> ).<\/span><\/li>\n
    •  \u062a\u062c\u0627\u0646\u0633 \u0627\u0644\u062a\u0628\u0627\u064a\u0646<\/strong> – \u0646\u062d\u062a\u0627\u062c \u0625\u0644\u0649 \u0627\u0644\u062a\u062d\u0642\u0642 \u0645\u0646 \u0623\u0646 \u0627\u0644\u062a\u0628\u0627\u064a\u0646\u0627\u062a \u0628\u064a\u0646 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0627\u062a \u0645\u062a\u0633\u0627\u0648\u064a\u0629<\/span><\/li>\n<\/ul>\n
       \u0644\u0644\u062a\u062d\u0642\u0642 \u0645\u0646 \u0623\u0646 \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0645\u0634\u062a\u0631\u0643 \u0648\u0627\u0644\u0639\u0644\u0627\u062c \u0645\u0633\u062a\u0642\u0644\u0627\u0646\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANOVA) \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0631\u062c\u0629 \u0627\u0644\u062d\u0627\u0644\u064a\u0629<\/em> \u0643\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0627\u0633\u062a\u062c\u0627\u0628\u0629 \u0648\u062a\u0642\u0646\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629<\/em> \u0643\u0645\u062a\u063a\u064a\u0631 \u0645\u062a\u0648\u0642\u0639:<\/span><\/p>\n
       #fit anova model\n<\/span>anova_model <- aov(current_grade ~ technique, data = data)\n#view summary of anova model\n<\/span>summary(anova_model)\n\n# Df Sum Sq Mean Sq F value Pr(>F)\n#technical 2 74 37.21 0.599 0.552\n#Residuals 87 5406 62.14    \n<\/strong><\/pre>\n
       \u0627\u0644\u0642\u064a\u0645\u0629 p \u0623\u0643\u0628\u0631 \u0645\u0646 0.05\u060c \u0648\u0628\u0627\u0644\u062a\u0627\u0644\u064a \u0641\u0625\u0646 \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0645\u0634\u062a\u0631\u0643 ( \u0627\u0644\u062f\u0631\u062c\u0629 \u0627\u0644\u062d\u0627\u0644\u064a\u0629)<\/em> \u0648\u0627\u0644\u0639\u0644\u0627\u062c ( \u062a\u0642\u0646\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629<\/em> ) \u064a\u0628\u062f\u0648\u0627\u0646 \u0645\u0633\u062a\u0642\u0644\u064a\u0646.<\/span><\/p>\n
       \u0648\u0645\u0646 \u062b\u0645\u060c \u0644\u0644\u062a\u0623\u0643\u062f \u0645\u0646 \u0648\u062c\u0648\u062f \u062a\u062c\u0627\u0646\u0633 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 \u0628\u064a\u0646 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0627\u062a\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0625\u062c\u0631\u0627\u0621 \u0627\u062e\u062a\u0628\u0627\u0631 \u0644\u064a\u0641\u064a\u0646:<\/span><\/p>\n
       #load car<\/em> library to conduct Levene's Test<\/span>\nlibary(car)\n\n#conduct Levene's Test<\/span>\nleveneTest(technical exam, data = data)\n\n#Levene's Test for Homogeneity of Variance (center = median)\n# Df F value Pr(>F)    \n#group 2 9.4324 0.0001961 ***\n#87   \n<\/strong><\/pre>\n
       \u0627\u0644\u0642\u064a\u0645\u0629 p \u0644\u0644\u0627\u062e\u062a\u0628\u0627\u0631 \u062a\u0633\u0627\u0648\u064a 0.0001961\u060c \u0645\u0645\u0627 \u064a\u0634\u064a\u0631 \u0625\u0644\u0649 \u0623\u0646 \u0627\u0644\u0641\u0631\u0648\u0642 \u0628\u064a\u0646 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0627\u062a \u063a\u064a\u0631 \u0645\u062a\u0633\u0627\u0648\u064a\u0629. \u0639\u0644\u0649 \u0627\u0644\u0631\u063a\u0645 \u0645\u0646 \u0623\u0646\u0647 \u064a\u0645\u0643\u0646\u0646\u0627 \u0645\u062d\u0627\u0648\u0644\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0648\u064a\u0644 \u0639\u0644\u0649 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0644\u062a\u0635\u062d\u064a\u062d \u0647\u0630\u0647 \u0627\u0644\u0645\u0634\u0643\u0644\u0629\u060c \u0625\u0644\u0627 \u0623\u0646\u0646\u0627 \u0644\u0646 \u0646\u0642\u0644\u0642 \u0643\u062b\u064a\u0631\u064b\u0627 \u0628\u0634\u0623\u0646 \u0627\u062e\u062a\u0644\u0627\u0641\u0627\u062a \u0627\u0644\u062a\u0628\u0627\u064a\u0646 \u0641\u064a \u0647\u0630\u0627 \u0627\u0644\u0648\u0642\u062a.<\/span><\/p>\n
       \u0627\u0644\u062e\u0637\u0648\u0629 3: \u0636\u0628\u0637 \u0646\u0645\u0648\u0630\u062c \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA).<\/strong><\/span><\/h3>\n
       \u0628\u0639\u062f \u0630\u0644\u0643\u060c \u0633\u0648\u0641 \u0646\u0644\u0627\u0626\u0645 \u0646\u0645\u0648\u0630\u062c \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 \u0627\u0644\u0645\u0634\u062a\u0631\u0643 (ANCOVA) \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u062f\u0631\u062c\u0629 \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646<\/em> \u0643\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0627\u0633\u062a\u062c\u0627\u0628\u0629\u060c \u0648\u062a\u0642\u0646\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629<\/em> \u0643\u0645\u062a\u063a\u064a\u0631 \u0645\u062a\u0646\u0628\u0626 (\u0623\u0648 “\u0639\u0644\u0627\u062c”)\u060c \u0648\u0627\u0644\u062f\u0631\u062c\u0629 \u0627\u0644\u062d\u0627\u0644\u064a\u0629<\/em> \u0643\u0645\u062a\u063a\u064a\u0631 \u0645\u0634\u062a\u0631\u0643.<\/span><\/p>\n
       \u0633\u0648\u0641 \u0646\u0633\u062a\u062e\u062f\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 Anova() \u0641\u064a \u0627\u0644\u062d\u0632\u0645\u0629 \u0644\u0623\u0646\u0647 \u0644\u0644\u0642\u064a\u0627\u0645 \u0628\u0630\u0644\u0643\u060c \u0641\u0642\u0637 \u0644\u0646\u0643\u0648\u0646 \u0642\u0627\u062f\u0631\u064a\u0646 \u0639\u0644\u0649 \u062a\u062d\u062f\u064a\u062f \u0623\u0646\u0646\u0627 \u0646\u0631\u064a\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u062c\u0645\u0648\u0639 \u0627\u0644\u0645\u0631\u0628\u0639\u0627\u062a \u0645\u0646 \u0627\u0644\u0646\u0648\u0639 \u0627\u0644\u062b\u0627\u0644\u062b \u0644\u0644\u0646\u0645\u0648\u0630\u062c\u060c \u0644\u0623\u0646 \u0627\u0644\u0646\u0648\u0639 \u0627\u0644\u0623\u0648\u0644 \u0645\u0646 \u0627\u0644\u0645\u0631\u0628\u0639\u0627\u062a \u064a\u0639\u062a\u0645\u062f \u0639\u0644\u0649 \u0627\u0644\u062a\u0631\u062a\u064a\u0628 \u0627\u0644\u0630\u064a \u0628\u0647 \u064a\u062a\u0645 \u0625\u062f\u062e\u0627\u0644 \u0627\u0644\u0645\u062a\u0646\u0628\u0626\u064a\u0646 \u0641\u064a \u0627\u0644\u0646\u0645\u0648\u0630\u062c:<\/span><\/p>\n
       #load car<\/em> library<\/span>\nlibrary(car)\n\n#fit ANCOVA model\n<\/span>ancova_model <- aov(exam ~ technique + current_grade, data = data)\n\n#view summary of model\n<\/span>Anova(ancova_model, type=\"III\") \n\n#Answer: exam\n# Sum Sq Df F value Pr(>F)    \n#(Intercept) 7161.2 1 201.4621 < 2.2e-16 ***\n#technical 1242.9 2 17.4830 4.255e-07 ***\n#current_grade 12.3 1 0.3467 0.5576    \n#Residuals 3057.0 86         \n<\/strong><\/pre>\n
       \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646 \u0627\u0644\u0642\u064a\u0645\u0629 p \u0644\u0644\u062a\u0642\u0646\u064a\u0629<\/em> \u0645\u0646\u062e\u0641\u0636\u0629 \u0644\u0644\u063a\u0627\u064a\u0629\u060c \u0645\u0645\u0627 \u064a\u0634\u064a\u0631 \u0625\u0644\u0649 \u0623\u0646 \u062a\u0642\u0646\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0644\u0647\u0627 \u062a\u0623\u062b\u064a\u0631 \u0630\u0648 \u062f\u0644\u0627\u0644\u0629 \u0625\u062d\u0635\u0627\u0626\u064a\u0629 \u0639\u0644\u0649 \u062f\u0631\u062c\u0627\u062a \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646\u0627\u062a\u060c \u062d\u062a\u0649 \u0628\u0639\u062f \u0627\u0644\u062a\u062d\u0643\u0645 \u0641\u064a \u0627\u0644\u062f\u0631\u062c\u0629 \u0627\u0644\u062d\u0627\u0644\u064a\u0629.<\/span><\/p>\n
       \u0627\u0644\u062e\u0637\u0648\u0629 4: \u0627\u062e\u062a\u0628\u0627\u0631 \u0645\u0627 \u0628\u0639\u062f \u0627\u0644\u0645\u062e\u0635\u0635<\/strong><\/span><\/h3>\n
       \u0639\u0644\u0649 \u0627\u0644\u0631\u063a\u0645 \u0645\u0646 \u0623\u0646 \u0646\u062a\u0627\u0626\u062c \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0623\u062e\u0628\u0631\u062a\u0646\u0627 \u0623\u0646 \u0623\u0633\u0644\u0648\u0628 \u0627\u0644\u062f\u0631\u0627\u0633\u0629<\/em> \u0643\u0627\u0646 \u0644\u0647 \u062a\u0623\u062b\u064a\u0631 \u0630\u0648 \u062f\u0644\u0627\u0644\u0629 \u0625\u062d\u0635\u0627\u0626\u064a\u0629 \u0639\u0644\u0649 \u062f\u0631\u062c\u0627\u062a \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646\u0627\u062a\u060c \u0625\u0644\u0627 \u0623\u0646\u0646\u0627 \u0628\u062d\u0627\u062c\u0629 \u0625\u0644\u0649 \u0625\u062c\u0631\u0627\u0621 \u0627\u062e\u062a\u0628\u0627\u0631 \u0645\u0627 \u0628\u0639\u062f \u0645\u062e\u0635\u0635 \u0644\u062a\u062d\u062f\u064a\u062f \u062a\u0642\u0646\u064a\u0627\u062a \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0627\u0644\u062a\u064a \u062a\u062e\u062a\u0644\u0641 \u0639\u0646 \u0628\u0639\u0636\u0647\u0627 \u0627\u0644\u0628\u0639\u0636.<\/span><\/p>\n
       \u0644\u0644\u0642\u064a\u0627\u0645 \u0628\u0630\u0644\u0643\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 glht()\u200e \u0641\u064a \u062d\u0632\u0645\u0629 multicomp<\/strong> \u0641\u064a R \u0644\u0625\u062c\u0631\u0627\u0621 \u0627\u062e\u062a\u0628\u0627\u0631 Tukey \u0644\u0625\u062c\u0631\u0627\u0621 \u0645\u0642\u0627\u0631\u0646\u0627\u062a \u0645\u062a\u0639\u062f\u062f\u0629:<\/span><\/p>\n
       #load the multcomp<\/em> library<\/span>\nlibrary(multicomp)\n\n#fit the ANCOVA model\n<\/span>ancova_model <- aov(exam ~ technique + current_grade, data = data)\n\n#define the post hoc comparisons to make\n<\/span>postHocs <- glht(ancova_model, linfct = mcp(technique = \"Tukey\"))\n\n#view a summary of the post hoc comparisons\n<\/span>summary(postHocs)\n\n#Multiple Comparisons of Means: Tukey Contrasts\n#\n#Fit: aov(formula = exam ~ technique + current_grade, data = data)\n#\n#Linear Assumptions:\n#Estimate Std. Error t value Pr(>|t|)    \n#B - A == 0 -6.711 1.540 -4.358 0.000109 ***\n#C - A == 0 -8.736 1.549 -5.640 < 1e-04 ***\n#C - B == 0 -2.025 1.545 -1.311 0.393089    \n\n#view the confidence intervals associated with the multiple comparisons\n<\/span>confint(postHocs)\n\n# Simultaneous Confidence Intervals\n#\n#Multiple Comparisons of Means: Tukey Contrasts\n#\n#Fit: aov(formula = exam ~ technique + current_grade, data = data)\n#\n#Quantile = 2.3845\n#95% family-wise confidence level\n#\n#Linear Assumptions:\n# Estimate lwr upr     \n#B - A == 0 -6.7112 -10.3832 -3.0392\n#C - A == 0 -8.7364 -12.4302 -5.0426\n#C - B == 0 -2.0252 -5.7091 1.6588\n<\/strong><\/pre>\n
       \u0648\u0645\u0646 \u0627\u0644\u0646\u062a\u064a\u062c\u0629 \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646 \u0647\u0646\u0627\u0643 \u0641\u0631\u0642 \u0630\u0648 \u062f\u0644\u0627\u0644\u0629 \u0625\u062d\u0635\u0627\u0626\u064a\u0629 (\u0639\u0646\u062f \u03b1 = 0.05) \u0641\u064a \u0646\u062a\u0627\u0626\u062c \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646 \u0628\u064a\u0646 \u062f\u0631\u0627\u0633\u0629 \u0627\u0644\u062a\u0642\u0646\u064a\u0629 \u0623<\/em> \u0648\u062f\u0631\u0627\u0633\u0629 \u0627\u0644\u062a\u0642\u0646\u064a\u0629 \u0628<\/em> (\u0627\u0644\u0642\u064a\u0645\u0629 \u0627\u0644\u0627\u062d\u062a\u0645\u0627\u0644\u064a\u0629: 0,000109) \u0648\u0643\u0630\u0644\u0643 \u0628\u064a\u0646 \u0627\u0644\u062a\u0642\u0646\u064a\u0629 \u0623<\/em> \u0648\u0627\u0644\u062a\u0642\u0646\u064a\u0629 \u062c<\/em> (\u0642\u064a\u0645\u0629 p: <1e-04).<\/span><\/p>\n
       \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u064a\u0636\u064b\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646\u0647 \u0644\u0627<\/em> \u064a\u0648\u062c\u062f \u0641\u0631\u0642 \u0630\u0648 \u062f\u0644\u0627\u0644\u0629 \u0625\u062d\u0635\u0627\u0626\u064a\u0629 (\u0639\u0646\u062f \u03b1 = 0.05) \u0628\u064a\u0646 \u0627\u0644\u062a\u0642\u0646\u064a\u0627\u062a B<\/em> \u0648 C.<\/em><\/span> \u0643\u0645\u0627 \u062a\u062f\u0639\u0645 \u0641\u062a\u0631\u0627\u062a \u0627\u0644\u062b\u0642\u0629 \u0628\u064a\u0646 \u0627\u0644\u062a\u0642\u0646\u064a\u0627\u062a \u0647\u0630\u0647 \u0627\u0644\u0646\u062a\u0627\u0626\u062c.<\/span><\/p>\n
       \u0648\u0628\u0627\u0644\u062a\u0627\u0644\u064a\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0633\u062a\u0646\u062a\u062c \u0623\u0646 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u062a\u0642\u0646\u064a\u0629 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 (\u0623)<\/em> \u064a\u0624\u062f\u064a \u0625\u0644\u0649 \u062f\u0631\u062c\u0629 \u0627\u0645\u062a\u062d\u0627\u0646 \u0623\u0639\u0644\u0649 \u0628\u0643\u062b\u064a\u0631 \u0625\u062d\u0635\u0627\u0626\u064a\u064b\u0627 \u0644\u0644\u0637\u0644\u0627\u0628 \u0645\u0642\u0627\u0631\u0646\u0629 \u0628\u0627\u0644\u062a\u0642\u0646\u064a\u0627\u062a (\u0628)<\/em> \u0648 (\u062c)<\/em> \u060c \u062d\u062a\u0649 \u0628\u0639\u062f \u0627\u0644\u062a\u062d\u0643\u0645 \u0641\u064a \u0627\u0644\u062f\u0631\u062c\u0629 \u0627\u0644\u062d\u0627\u0644\u064a\u0629 \u0644\u0644\u0637\u0627\u0644\u0628 \u0641\u064a \u0627\u0644\u0641\u0635\u0644.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
      \u064a\u0642\u062f\u0645 \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0645\u062b\u0627\u0644\u0627\u064b \u0644\u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0641\u064a R. \u0645\u062b\u0627\u0644: \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0641\u064a R \u0633\u0646\u0642\u0648\u0645 \u0628\u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0644\u0627\u062e\u062a\u0628\u0627\u0631 \u0645\u0627 \u0625\u0630\u0627 \u0643\u0627\u0646 \u0623\u0633\u0644\u0648\u0628 \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0644\u0647 \u062a\u0623\u062b\u064a\u0631 \u0639\u0644\u0649 \u0646\u062a\u0627\u0626\u062c \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646 \u0623\u0645 \u0644\u0627 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0627\u0644\u062a\u0627\u0644\u064a\u0629: \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0627\u0644\u0641\u0646\u064a\u0629 : \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0645\u0633\u062a\u0642\u0644 \u0627\u0644\u0630\u064a \u0646\u0631\u063a\u0628 \u0641\u064a \u062a\u062d\u0644\u064a\u0644\u0647 \u062f\u0631\u062c\u0629 \u0627\u0644\u0637\u0627\u0644\u0628 \u0627\u0644\u062d\u0627\u0644\u064a\u0629 : \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0645\u0634\u062a\u0631\u0643 \u0627\u0644\u0630\u064a […]<\/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":[],"yoast_head":"\n\u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0641\u064a R - \u0639\u0644\u0645 \u0627\u0644\u0625\u062d\u0635\u0627\u0621<\/title>\n<meta name=\"description\" content=\"\u064a\u0634\u0631\u062d \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0641\u064a R.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/ar\/\u0627\u0654\u0646\u0643\u0648\u0641\u0627-\u0641\u064a-\u0635\/\" \/>\n<meta property=\"og:locale\" content=\"az_AZ\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0641\u064a R - \u0639\u0644\u0645 \u0627\u0644\u0625\u062d\u0635\u0627\u0621\" \/>\n<meta property=\"og:description\" content=\"\u064a\u0634\u0631\u062d \u0647\u0630\u0627 \u0627\u0644\u0628\u0631\u0646\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a \u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0641\u064a R.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/ar\/\u0627\u0654\u0646\u0643\u0648\u0641\u0627-\u0641\u064a-\u0635\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-29T18:17:31+00:00\" \/>\n<meta name=\"author\" content=\"\u062f\u0643\u062a\u0648\u0631 \u0628\u0646\u064a\u0627\u0645\u064a\u0646 \u0623\u0646\u062f\u0631\u0633\u0648\u0646\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u062f\u0643\u062a\u0648\u0631 \u0628\u0646\u064a\u0627\u0645\u064a\u0646 \u0623\u0646\u062f\u0631\u0633\u0648\u0646\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/ar\/%d8%a7%d9%94%d9%86%d9%83%d9%88%d9%81%d8%a7-%d9%81%d9%8a-%d8%b5\/\",\"url\":\"https:\/\/statorials.org\/ar\/%d8%a7%d9%94%d9%86%d9%83%d9%88%d9%81%d8%a7-%d9%81%d9%8a-%d8%b5\/\",\"name\":\"\u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u0627\u0644\u062a\u0628\u0627\u064a\u0646 (ANCOVA) \u0641\u064a R - 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