{"id":4267,"date":"2023-07-12T10:05:09","date_gmt":"2023-07-12T10:05:09","guid":{"rendered":"https:\/\/statorials.org\/ar\/%d9%85%d8%ac%d9%85%d9%88%d8%b9%d8%a9-%d9%81%d8%b1%d8%b9%d9%8a%d8%a9-%d9%85-%d9%81%d9%8a-%d8%b5\/"},"modified":"2023-07-12T10:05:09","modified_gmt":"2023-07-12T10:05:09","slug":"%d9%85%d8%ac%d9%85%d9%88%d8%b9%d8%a9-%d9%81%d8%b1%d8%b9%d9%8a%d8%a9-%d9%85-%d9%81%d9%8a-%d8%b5","status":"publish","type":"post","link":"https:\/\/statorials.org\/ar\/%d9%85%d8%ac%d9%85%d9%88%d8%b9%d8%a9-%d9%81%d8%b1%d8%b9%d9%8a%d8%a9-%d9%85-%d9%81%d9%8a-%d8%b5\/","title":{"rendered":"\u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u062c\u0645\u0648\u0639\u0629 \u0641\u0631\u0639\u064a\u0629 \u0645\u0646 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0645\u0639 \u0648\u0638\u064a\u0641\u0629 lm() \u0641\u064a r"},"content":{"rendered":"

<\/p>\n

\n

\u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0648\u0633\u064a\u0637\u0629 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0641\u0631\u0639\u064a\u0629<\/strong> \u0644\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u062c\u0645\u0648\u0639\u0629 \u0641\u0631\u0639\u064a\u0629 \u0641\u0642\u0637 \u0645\u0646 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0639\u0646\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 lm()<\/a> \u0644\u062a\u0646\u0627\u0633\u0628 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0641\u064a R:<\/span><\/p>\n

 fit <- lm(points ~ fouls + minutes, data=df, subset=(minutes><\/span> 10<\/span> ))<\/span><\/strong><\/pre>\n
 \u064a\u062a\u0648\u0627\u0641\u0642 \u0647\u0630\u0627 \u0627\u0644\u0645\u062b\u0627\u0644 \u0627\u0644\u0645\u062d\u062f\u062f \u0645\u0639 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u0630\u064a \u064a\u0633\u062a\u062e\u062f\u0645 \u0627\u0644\u0646\u0642\u0627\u0637<\/strong> \u0643\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u0627\u0633\u062a\u062c\u0627\u0628\u0629 \u0648\u0627\u0644\u062d\u0634\u0648\u062f<\/strong> \u0648\u0627\u0644\u062f\u0642\u0627\u0626\u0642<\/strong> \u0643\u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0645\u062a\u0648\u0642\u0639\u0629.<\/span><\/p>\n
 \u062a\u062d\u062f\u062f \u0648\u0633\u064a\u0637\u0629 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0641\u0631\u0639\u064a\u0629<\/strong> \u0623\u0646\u0647 \u064a\u062c\u0628 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0635\u0641\u0648\u0641 \u0641\u0642\u0637 \u0641\u064a \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u062d\u064a\u062b \u064a\u0643\u0648\u0646 \u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u062f\u0642\u0627\u0626\u0642<\/strong> \u0623\u0643\u0628\u0631 \u0645\u0646 10 \u0639\u0646\u062f \u0645\u0644\u0627\u0621\u0645\u0629 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631.<\/span><\/p>\n
 \u064a\u0648\u0636\u062d \u0627\u0644\u0645\u062b\u0627\u0644 \u0627\u0644\u062a\u0627\u0644\u064a \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0628\u0646\u0627\u0621 \u0627\u0644\u062c\u0645\u0644\u0629 \u0647\u0630\u0627 \u0639\u0645\u0644\u064a\u064b\u0627.<\/span><\/p>\n
 \u0645\u062b\u0627\u0644: \u0643\u064a\u0641\u064a\u0629 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0645\u062c\u0645\u0648\u0639\u0629 \u0641\u0631\u0639\u064a\u0629 \u0645\u0646 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0645\u0639 lm() \u0641\u064a R<\/strong><\/span><\/h2>\n
 \u0644\u0646\u0641\u062a\u0631\u0636 \u0623\u0646 \u0644\u062f\u064a\u0646\u0627 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u062a\u0627\u0644\u064a \u0641\u064a R \u0627\u0644\u0630\u064a \u064a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0645\u0639\u0644\u0648\u0645\u0627\u062a \u062d\u0648\u0644 \u062f\u0642\u0627\u0626\u0642 \u0627\u0644\u0644\u0639\u0628\u060c \u0648\u0625\u062c\u0645\u0627\u0644\u064a \u0627\u0644\u0623\u062e\u0637\u0627\u0621\u060c \u0648\u0625\u062c\u0645\u0627\u0644\u064a \u0627\u0644\u0646\u0642\u0627\u0637 \u0627\u0644\u062a\u064a \u0633\u062c\u0644\u0647\u0627 10 \u0644\u0627\u0639\u0628\u064a \u0643\u0631\u0629 \u0633\u0644\u0629:<\/span><\/p>\n
 #create data frame\n<\/span>df <- data. frame<\/span> (minutes=c(5, 10, 13, 14, 20, 22, 26, 34, 38, 40),\n                 fouls=c(5, 5, 3, 4, 2, 1, 3, 2, 1, 1),\n                 points=c(6, 8, 8, 7, 14, 10, 22, 24, 28, 30))\n\n#view data frame\n<\/span>df\n\n   minutes fouls points\n1 5 5 6\n2 10 5 8\n3 13 3 8\n4 14 4 7\n5 20 2 14\n6 22 1 10\n7 26 3 22\n8 34 2 24\n9 38 1 28\n10 40 1 30<\/strong><\/pre>\n
 \u0644\u0646\u0641\u062a\u0631\u0636 \u0623\u0646\u0646\u0627 \u0646\u0631\u064a\u062f \u0645\u0644\u0627\u0621\u0645\u0629 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u062e\u0637\u064a \u0627\u0644\u0645\u062a\u0639\u062f\u062f \u0627\u0644\u062a\u0627\u0644\u064a:<\/span><\/p>\n
 \u0627\u0644\u0646\u0642\u0627\u0637 = \u03b2 0<\/sub> + \u03b2 1<\/sub> (\u062f\u0642\u0627\u0626\u0642) + \u03b2 2<\/sub> (\u0627\u0644\u0623\u062e\u0637\u0627\u0621)<\/strong><\/span><\/p>\n
 \u0648\u0645\u0639 \u0630\u0644\u0643\u060c \u0644\u0646\u0641\u062a\u0631\u0636 \u0623\u0646\u0646\u0627 \u0646\u0631\u064a\u062f \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u0645\u0648\u062c\u0648\u062f\u0629 \u0641\u064a \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0641\u0642\u0637 \u062d\u064a\u062b \u064a\u0643\u0648\u0646 \u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u062f\u0642\u0627\u0626\u0642<\/strong> \u0623\u0643\u0628\u0631 \u0645\u0646 10.<\/span><\/p>\n
 \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 lm()<\/strong> \u0645\u0639 \u0648\u0633\u064a\u0637\u0629 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0641\u0631\u0639\u064a\u0629<\/strong> \u0644\u062a\u0646\u0627\u0633\u0628 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0647\u0630\u0627:<\/span><\/p>\n
 #fit multiple linear regression model (only for rows where minutes>10)\n<\/span><\/strong>fit <- lm(points ~ fouls + minutes, data=df, subset=(minutes><\/span> 10<\/span> ))\n\n#view model summary<\/span>\nsummary(fit)\n\nCall:\nlm(formula = points ~ fouls + minutes, data = df, subset = (minutes > \n    10))\n\nResiduals:\n      3 4 5 6 7 8 9 10 \n 1.2824 -2.5882 2.2000 -1.9118 2.3588 -1.7176 0.1824 0.1941 \n\nCoefficients:\n            Estimate Std. Error t value Pr(>|t|)    \n(Intercept) -11.8353 4.9696 -2.382 0.063046 .  \nfouls 1.8765 1.0791 1.739 0.142536    \nminutes 0.9941 0.1159 8.575 0.000356 ***\n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 2.255 on 5 degrees of freedom\nMultiple R-squared: 0.9574, Adjusted R-squared: 0.9404 \nF-statistic: 56.19 on 2 and 5 DF, p-value: 0.0003744\n<\/span><\/strong><\/pre>\n
 \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062f\u0627\u0644\u0629 nobs()<\/strong> \u0644\u0645\u0639\u0631\u0641\u0629 \u0639\u062f\u062f \u0627\u0644\u0645\u0644\u0627\u062d\u0638\u0627\u062a \u0645\u0646 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u062a\u064a \u062a\u0645 \u0627\u0633\u062a\u062e\u062f\u0627\u0645\u0647\u0627 \u0628\u0627\u0644\u0641\u0639\u0644 \u0644\u062a\u0646\u0627\u0633\u0628 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631:<\/span><\/p>\n
 #view number of observations used to fit model\n<\/span>nobs(fit)\n\n[1] 8\n<\/span><\/span><\/strong><\/pre>\n
 \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646\u0647 \u062a\u0645 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 8<\/strong> \u0635\u0641\u0648\u0641 \u0645\u0646 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0644\u062a\u0646\u0627\u0633\u0628 \u0627\u0644\u0646\u0645\u0648\u0630\u062c.<\/span><\/p>\n
 \u0625\u0630\u0627 \u0646\u0638\u0631\u0646\u0627 \u0625\u0644\u0649 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u0623\u0635\u0644\u064a\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646 8<\/strong> \u0635\u0641\u0648\u0641 \u0628\u0627\u0644\u0636\u0628\u0637 \u0643\u0627\u0646\u062a \u0644\u0647\u0627 \u0642\u064a\u0645\u0629 \u0623\u0643\u0628\u0631 \u0645\u0646 10 \u0644\u0645\u062a\u063a\u064a\u0631 \u0627\u0644\u062f\u0642\u0627\u0626\u0642<\/strong> \u060c \u0645\u0645\u0627 \u064a\u0639\u0646\u064a \u0623\u0646\u0647 \u062a\u0645 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u062a\u0644\u0643 \u0627\u0644\u0635\u0641\u0648\u0641 \u0641\u0642\u0637 \u0639\u0646\u062f \u0645\u0644\u0627\u0621\u0645\u0629 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631.<\/span><\/p>\n
 \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u064a\u0636\u064b\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0639\u0627\u0645\u0644 \u0627\u0644\u062a\u0634\u063a\u064a\u0644 &<\/strong> \u0641\u064a \u0648\u0633\u064a\u0637\u0629 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0629 \u0627\u0644\u0641\u0631\u0639\u064a\u0629<\/strong> \u0644\u062a\u0639\u064a\u064a\u0646 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0641\u0631\u0639\u064a\u064b\u0627 \u0628\u0646\u0627\u0621\u064b \u0639\u0644\u0649 \u0634\u0631\u0648\u0637 \u0645\u062a\u0639\u062f\u062f\u0629.<\/span><\/p>\n
 \u0639\u0644\u0649 \u0633\u0628\u064a\u0644 \u0627\u0644\u0645\u062b\u0627\u0644\u060c \u064a\u0645\u0643\u0646\u0646\u0627 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0635\u064a\u063a\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0644\u062a\u0646\u0627\u0633\u0628 \u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0635\u0641\u0648\u0641 \u0627\u0644\u0645\u0648\u062c\u0648\u062f\u0629 \u0641\u064a \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0641\u0642\u0637 \u062d\u064a\u062b \u062a\u0643\u0648\u0646 \u0627\u0644\u062f\u0642\u0627\u0626\u0642<\/strong> \u0623\u0643\u0628\u0631 \u0645\u0646 10 \u0648\u0627\u0644\u0623\u062e\u0637\u0627\u0621<\/strong> \u0623\u0642\u0644 \u0645\u0646 4:<\/span><\/p>\n
 #fit multiple linear regression model (only where minutes>10 & fouls<4)\n<\/span><\/strong>fit <- lm(points ~ fouls + minutes, data=df, subset=(minutes><\/span> 10 &<\/span> fouls< 4<\/span><\/span><\/span> ))\n\n#view number of observations used to fit model<\/span>\nnobs(fit)\n\n[1] 7\n<\/span><\/strong><\/pre>\n
 \u0645\u0646 \u0627\u0644\u0646\u062a\u064a\u062c\u0629 \u064a\u0645\u0643\u0646\u0646\u0627 \u0623\u0646 \u0646\u0631\u0649 \u0623\u0646\u0647 \u062a\u0645 \u0627\u0633\u062a\u062e\u062f\u0627\u0645 7<\/strong> \u0635\u0641\u0648\u0641 \u0645\u0646 \u0625\u0637\u0627\u0631 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0644\u062a\u0646\u0627\u0633\u0628 \u0647\u0630\u0627 \u0627\u0644\u0646\u0645\u0648\u0630\u062c \u0627\u0644\u0645\u0639\u064a\u0646.<\/span><\/p>\n
 \u0645\u0635\u0627\u062f\u0631 \u0625\u0636\u0627\u0641\u064a\u0629<\/strong><\/span><\/h2>\n
 \u062a\u0634\u0631\u062d \u0627\u0644\u0628\u0631\u0627\u0645\u062c \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u064a\u0629 \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0643\u064a\u0641\u064a\u0629 \u062a\u0646\u0641\u064a\u0630 \u0627\u0644\u0645\u0647\u0627\u0645 \u0627\u0644\u0634\u0627\u0626\u0639\u0629 \u0627\u0644\u0623\u062e\u0631\u0649 \u0641\u064a R:<\/span><\/p>\n
 \u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u062e\u0637\u064a \u0627\u0644\u0628\u0633\u064a\u0637 \u0641\u064a R<\/a>
 \u0643\u064a\u0641\u064a\u0629 \u0625\u062c\u0631\u0627\u0621 \u0627\u0644\u0627\u0646\u062d\u062f\u0627\u0631 \u0627\u0644\u062e\u0637\u064a \u0627\u0644\u0645\u062a\u0639\u062f\u062f \u0641\u064a R<\/a>
 \u0643\u064a\u0641\u064a\u0629 \u0625\u0646\u0634\u0627\u0621 \u0642\u0637\u0639\u0629 \u0623\u0631\u0636 \u0645\u062a\u0628\u0642\u064a\u0629 \u0641\u064a R<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
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