{"id":2456,"date":"2023-07-22T04:43:11","date_gmt":"2023-07-22T04:43:11","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d8%aa%d8%ad%d9%84%d9%8a%d9%84-%d8%ab%d9%86%d8%a7%d9%8a%d9%94%d9%8a-%d8%a7%d9%84%d9%85%d8%aa%d8%ba%d9%8a%d8%b1-%d9%81%d9%8a-%d8%b5\/"},"modified":"2023-07-22T04:43:11","modified_gmt":"2023-07-22T04:43:11","slug":"%d8%aa%d8%ad%d9%84%d9%8a%d9%84-%d8%ab%d9%86%d8%a7%d9%8a%d9%94%d9%8a-%d8%a7%d9%84%d9%85%d8%aa%d8%ba%d9%8a%d8%b1-%d9%81%d9%8a-%d8%b5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/%d8%aa%d8%ad%d9%84%d9%8a%d9%84-%d8%ab%d9%86%d8%a7%d9%8a%d9%94%d9%8a-%d8%a7%d9%84%d9%85%d8%aa%d8%ba%d9%8a%d8%b1-%d9%81%d9%8a-%d8%b5\/","title":{"rendered":"\u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u062a\u062d\u0644\u064a\u0644 \u062b\u0646\u0627\u0626\u064a \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0641\u064a \u0644\u063a\u0629 r (\u0645\u0639 \u0623\u0645\u062b\u0644\u0629)"},"content":{"rendered":"

<\/p>\n

\n

\u064a\u0634\u064a\u0631 \u0645\u0635\u0637\u0644\u062d \u0627\u0644\u062a\u062d\u0644\u064a\u0644 \u062b\u0646\u0627\u0626\u064a \u0627\u0644\u0645\u062a\u063a\u064a\u0631<\/strong> \u0625\u0644\u0649 \u062a\u062d\u0644\u064a\u0644 \u0645\u062a\u063a\u064a\u0631\u064a\u0646. \u064a\u0645\u0643\u0646\u0643 \u062a\u0630\u0643\u0631 \u0630\u0644\u0643 \u0644\u0623\u0646 \u0627\u0644\u0628\u0627\u062f\u0626\u0629 “bi” \u062a\u0639\u0646\u064a “\u0627\u062b\u0646\u064a\u0646”.<\/span><\/p>\n

\u0627\u0644\u0647\u062f\u0641 \u0645\u0646 \u0627\u0644\u062a\u062d\u0644\u064a\u0644 \u062b\u0646\u0627\u0626\u064a \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0647\u0648 \u0641\u0647\u0645 \u0627\u0644\u0639\u0644\u0627\u0642\u0629 \u0628\u064a\u0646 \u0645\u062a\u063a\u064a\u0631\u064a\u0646<\/span><\/p>\n

\u0647\u0646\u0627\u0643 \u062b\u0644\u0627\u062b \u0637\u0631\u0642 \u0634\u0627\u0626\u0639\u0629 \u0644\u0625\u062c\u0631\u0627\u0621 \u0627\u0644\u062a\u062d\u0644\u064a\u0644 \u062b\u0646\u0627\u0626\u064a \u0627\u0644\u0645\u062a\u063a\u064a\u0631:<\/span><\/p>\n

1.<\/strong> \u0646\u0642\u0637\u0629 \u0627\u0644\u063a\u064a\u0648\u0645<\/span><\/p>\n

2.<\/strong> \u0645\u0639\u0627\u0645\u0644\u0627\u062a \u0627\u0644\u0627\u0631\u062a\u0628\u0627\u0637<\/span><\/p>\n

3.<\/strong> \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u062e\u0637\u064a \u0627\u0644\u0628\u0633\u064a\u0637<\/span><\/p>\n

\u064a\u0648\u0636\u062d \u0627\u0644\u0645\u062b\u0627\u0644 \u0627\u0644\u062a\u0627\u0644\u064a \u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u0643\u0644 \u0646\u0648\u0639 \u0645\u0646 \u0647\u0630\u0647 \u0627\u0644\u0623\u0646\u0648\u0627\u0639 \u0645\u0646 \u0627\u0644\u062a\u062d\u0644\u064a\u0644 \u062b\u0646\u0627\u0626\u064a \u0627\u0644\u0645\u062a\u063a\u064a\u0631 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0627\u0644\u062a\u064a \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0645\u0639\u0644\u0648\u0645\u0627\u062a \u062d\u0648\u0644 \u0645\u062a\u063a\u064a\u0631\u064a\u0646: (1)<\/strong> \u0627\u0644\u0633\u0627\u0639\u0627\u062a \u0627\u0644\u0645\u0633\u062a\u063a\u0631\u0642\u0629 \u0641\u064a \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0648 (2)<\/strong> \u062f\u0631\u062c\u0627\u062a \u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631 \u0627\u0644\u062a\u064a \u062d\u0635\u0644 \u0639\u0644\u064a\u0647\u0627 20 \u0637\u0627\u0644\u0628\u064b\u0627 \u0645\u062e\u062a\u0644\u0641\u064b\u0627:<\/span><\/p>\n

 #create data frame<\/span>\ndf <- data. frame<\/span> (hours=c(1, 1, 1, 2, 2, 2, 3, 3, 3, 3,\n                         3, 4, 4, 5, 5, 6, 6, 6, 7, 8),\n                 score=c(75, 66, 68, 74, 78, 72, 85, 82, 90, 82,\n                         80, 88, 85, 90, 92, 94, 94, 88, 91, 96))\n\n#view first six rows of data frame\n<\/span>head(df)\n\n  hours score\n1 1 75\n2 1 66\n3 1 68\n4 2 74\n5 2 78\n6 2 72<\/strong><\/pre>\n
 1. \u0646\u0642\u0637\u0629 \u0627\u0644\u063a\u064a\u0648\u0645<\/strong><\/span><\/h3>\n
 \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0627\u0644\u062a\u0627\u0644\u064a \u0644\u0625\u0646\u0634\u0627\u0621 \u0645\u062e\u0637\u0637 \u0645\u0628\u0639\u062b\u0631 \u0644\u0633\u0627\u0639\u0627\u062a \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0645\u0642\u0627\u0628\u0644 \u062f\u0631\u062c\u0629 \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646 \u0641\u064a R:<\/span> <\/p>\n
 #create scatterplot of hours studied vs. exam score<\/span>\nplot(df$hours, df$score, pch= 16<\/span> , col=' steelblue<\/span> ',\n     main=' Hours Studied vs. Exam Score<\/span> ',\n     xlab=' Hours Studied<\/span> ', ylab=' Exam Score<\/span> ')\n<\/strong><\/pre>\n
\"\"<\/p>\n
 \u064a\u064f\u0638\u0647\u0631 \u0627\u0644\u0645\u062d\u0648\u0631 “\u0633” \u0627\u0644\u0633\u0627\u0639\u0627\u062a \u0627\u0644\u062a\u064a \u062a\u0645\u062a \u062f\u0631\u0627\u0633\u062a\u0647\u0627\u060c \u0628\u064a\u0646\u0645\u0627 \u064a\u064f\u0638\u0647\u0631 \u0627\u0644\u0645\u062d\u0648\u0631 “\u0635” \u0627\u0644\u062f\u0631\u062c\u0629 \u0627\u0644\u062a\u064a \u062a\u0645 \u0627\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u064a\u0647\u0627 \u0641\u064a \u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631.<\/span><\/p>\n
 \u0648\u064a\u0628\u064a\u0646 \u0627\u0644\u0631\u0633\u0645 \u0627\u0644\u0628\u064a\u0627\u0646\u064a \u0623\u0646 \u0647\u0646\u0627\u0643 \u0639\u0644\u0627\u0642\u0629 \u0625\u064a\u062c\u0627\u0628\u064a\u0629 \u0628\u064a\u0646 \u0627\u0644\u0645\u062a\u063a\u064a\u0631\u064a\u0646: \u0641\u0643\u0644\u0645\u0627 \u0632\u0627\u062f \u0639\u062f\u062f \u0633\u0627\u0639\u0627\u062a \u0627\u0644\u062f\u0631\u0627\u0633\u0629\u060c \u062a\u0645\u064a\u0644 \u062f\u0631\u062c\u0627\u062a \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646\u0627\u062a \u0623\u064a\u0636\u0627 \u0625\u0644\u0649 \u0627\u0644\u0627\u0631\u062a\u0641\u0627\u0639.<\/span><\/p>\n
 2. \u0645\u0639\u0627\u0645\u0644\u0627\u062a \u0627\u0644\u0627\u0631\u062a\u0628\u0627\u0637<\/strong><\/span><\/h3>\n
 \u0645\u0639\u0627\u0645\u0644 \u0627\u0631\u062a\u0628\u0627\u0637 \u0628\u064a\u0631\u0633\u0648\u0646 \u0647\u0648 \u0648\u0633\u064a\u0644\u0629 \u0644\u0642\u064a\u0627\u0633 \u0627\u0644\u0639\u0644\u0627\u0642\u0629 \u0627\u0644\u062e\u0637\u064a\u0629 \u0628\u064a\u0646 \u0645\u062a\u063a\u064a\u0631\u064a\u0646.<\/span><\/p>\n
 \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 cor()<\/strong> \u0641\u064a R \u0644\u062d\u0633\u0627\u0628 \u0645\u0639\u0627\u0645\u0644 \u0627\u0631\u062a\u0628\u0627\u0637 \u0628\u064a\u0631\u0633\u0648\u0646 \u0628\u064a\u0646 \u0645\u062a\u063a\u064a\u0631\u064a\u0646:<\/span><\/p>\n
 #calculate correlation between hours studied and exam score received\n<\/span>cor(df$hours, df$score)\n\n[1] 0.891306\n<\/strong><\/pre>\n
 \u0648\u062a\u0628\u064a\u0646 \u0623\u0646 \u0645\u0639\u0627\u0645\u0644 \u0627\u0644\u0627\u0631\u062a\u0628\u0627\u0637 \u0647\u0648 0.891<\/strong> .<\/span><\/p>\n
 \u0647\u0630\u0647 \u0627\u0644\u0642\u064a\u0645\u0629 \u0642\u0631\u064a\u0628\u0629 \u0645\u0646 1\u060c \u0645\u0645\u0627 \u064a\u0634\u064a\u0631 \u0625\u0644\u0649 \u0648\u062c\u0648\u062f \u0639\u0644\u0627\u0642\u0629 \u0625\u064a\u062c\u0627\u0628\u064a\u0629 \u0642\u0648\u064a\u0629 \u0628\u064a\u0646 \u0633\u0627\u0639\u0627\u062a \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0648\u062f\u0631\u062c\u0629 \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646.<\/span><\/p>\n
 3. \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u062e\u0637\u064a \u0627\u0644\u0628\u0633\u064a\u0637<\/strong><\/span><\/h3>\n
 \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u062e\u0637\u064a \u0627\u0644\u0628\u0633\u064a\u0637 \u0647\u0648 \u0637\u0631\u064a\u0642\u0629 \u0625\u062d\u0635\u0627\u0626\u064a\u0629 \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645\u0647\u0627 \u0644\u0644\u0639\u062b\u0648\u0631 \u0639\u0644\u0649 \u0645\u0639\u0627\u062f\u0644\u0629 \u0627\u0644\u062e\u0637 \u0627\u0644\u0630\u064a “\u064a\u0646\u0627\u0633\u0628” \u0645\u062c\u0645\u0648\u0639\u0629 \u0645\u0646 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0628\u0634\u0643\u0644 \u0623\u0641\u0636\u0644\u060c \u0648\u0627\u0644\u062a\u064a \u064a\u0645\u0643\u0646\u0646\u0627 \u0628\u0639\u062f \u0630\u0644\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645\u0647\u0627 \u0644\u0641\u0647\u0645 \u0627\u0644\u0639\u0644\u0627\u0642\u0629 \u0627\u0644\u062f\u0642\u064a\u0642\u0629 \u0628\u064a\u0646 \u0645\u062a\u063a\u064a\u0631\u064a\u0646.<\/span><\/p>\n
 \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 lm()<\/strong> \u0641\u064a R \u0644\u062a\u0646\u0627\u0633\u0628 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u062e\u0637\u064a \u0627\u0644\u0628\u0633\u064a\u0637<\/a> \u0644\u0633\u0627\u0639\u0627\u062a \u0627\u0644\u062f\u0631\u0627\u0633\u0629 \u0648\u0646\u062a\u0627\u0626\u062c \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646\u0627\u062a \u0627\u0644\u0645\u0633\u062a\u0644\u0645\u0629:<\/span><\/p>\n
 #fit simple linear regression model\n<\/span>fit <- lm(score ~ hours, data=df)\n\n#view summary of model\n<\/span>summary(fit)\n\nCall:\nlm(formula = score ~ hours, data = df)\n\nResiduals:\n   Min 1Q Median 3Q Max \n-6,920 -3,927 1,309 1,903 9,385 \n\nCoefficients:\n            Estimate Std. Error t value Pr(>|t|)    \n(Intercept) 69.0734 1.9651 35.15 < 2nd-16 ***\nhours 3.8471 0.4613 8.34 1.35e-07 ***\n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 4.171 on 18 degrees of freedom\nMultiple R-squared: 0.7944, Adjusted R-squared: 0.783 \nF-statistic: 69.56 on 1 and 18 DF, p-value: 1.347e-07<\/strong><\/pre>\n
 \u0648\u062a\u0628\u064a\u0646 \u0623\u0646 \u0645\u0639\u0627\u062f\u0644\u0629 \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u0645\u062c\u0647\u0632\u0629 \u0647\u064a:<\/span><\/p>\n
 \u062f\u0631\u062c\u0629 \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646 = 69.0734 + 3.8471*(\u0633\u0627\u0639\u0627\u062a \u0627\u0644\u062f\u0631\u0627\u0633\u0629)<\/span><\/p>\n
 \u0648\u0647\u0630\u0627 \u064a\u062e\u0628\u0631\u0646\u0627 \u0623\u0646 \u0643\u0644 \u0633\u0627\u0639\u0629 \u0625\u0636\u0627\u0641\u064a\u0629 \u062a\u062a\u0645 \u062f\u0631\u0627\u0633\u062a\u0647\u0627 \u062a\u0631\u062a\u0628\u0637 \u0628\u0645\u062a\u0648\u0633\u0637 \u0632\u064a\u0627\u062f\u0629 \u0642\u062f\u0631\u0647\u0627 3.8471<\/strong> \u0641\u064a \u062f\u0631\u062c\u0629 \u0627\u0644\u0627\u0645\u062a\u062d\u0627\u0646.<\/span><\/p>\n
 \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u064a\u0636\u064b\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u0639\u0627\u062f\u0644\u0629 \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u0645\u062c\u0647\u0632\u0629 \u0644\u0644\u062a\u0646\u0628\u0624 \u0628\u0627\u0644\u0646\u062a\u064a\u062c\u0629 \u0627\u0644\u062a\u064a \u0633\u064a\u062d\u0635\u0644 \u0639\u0644\u064a\u0647\u0627 \u0627\u0644\u0637\u0627\u0644\u0628 \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0625\u062c\u0645\u0627\u0644\u064a \u0639\u062f\u062f \u0627\u0644\u0633\u0627\u0639\u0627\u062a \u0627\u0644\u0645\u062f\u0631\u0648\u0633\u0629.<\/span><\/p>\n
 \u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644 \u0627\u0644\u0637\u0627\u0644\u0628 \u0627\u0644\u0630\u064a \u064a\u062f\u0631\u0633 \u0644\u0645\u062f\u0629 3 \u0633\u0627\u0639\u0627\u062a \u064a\u062c\u0628 \u0623\u0646 \u064a\u062d\u0635\u0644 \u0639\u0644\u0649 81.6147<\/strong> :<\/span><\/p>\n