{"id":2086,"date":"2023-07-23T18:03:32","date_gmt":"2023-07-23T18:03:32","guid":{"rendered":"https:\/\/statorials.org\/uk\/%d0%bf%d1%96%d0%b4%d1%81%d1%83%d0%bc%d0%ba%d0%be%d0%b2%d0%b0-%d1%84%d1%83%d0%bd%d0%ba%d1%86%d1%96%d1%8f-%d0%b2-r\/"},"modified":"2023-07-23T18:03:32","modified_gmt":"2023-07-23T18:03:32","slug":"%d0%bf%d1%96%d0%b4%d1%81%d1%83%d0%bc%d0%ba%d0%be%d0%b2%d0%b0-%d1%84%d1%83%d0%bd%d0%ba%d1%86%d1%96%d1%8f-%d0%b2-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/uk\/%d0%bf%d1%96%d0%b4%d1%81%d1%83%d0%bc%d0%ba%d0%be%d0%b2%d0%b0-%d1%84%d1%83%d0%bd%d0%ba%d1%86%d1%96%d1%8f-%d0%b2-r\/","title":{"rendered":"\u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0443 r (\u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438)"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u0424\u0443\u043d\u043a\u0446\u0456\u044e <strong>summary()<\/strong> \u0443 R \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0434\u043b\u044f \u0448\u0432\u0438\u0434\u043a\u043e\u0433\u043e \u043f\u0456\u0434\u0441\u0443\u043c\u043e\u0432\u0443\u0432\u0430\u043d\u043d\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 \u0432\u0435\u043a\u0442\u043e\u0440\u0456, \u043a\u0430\u0434\u0440\u0456 \u0434\u0430\u043d\u0438\u0445, \u043c\u043e\u0434\u0435\u043b\u0456 \u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0457 \u0430\u0431\u043e \u043c\u043e\u0434\u0435\u043b\u0456 ANOVA \u0432 R.<\/span><\/p>\n<p> <span style=\"color: #000000;\">\u0426\u0435\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454 \u0442\u0430\u043a\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>summary(data)<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438 \u043f\u043e\u043a\u0430\u0437\u0443\u044e\u0442\u044c, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0446\u044e \u0444\u0443\u043d\u043a\u0446\u0456\u044e \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456.<\/span><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 1: \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f summary() \u0456\u0437 Vector<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e <strong>summary()<\/strong> \u0434\u043b\u044f \u043f\u0456\u0434\u0441\u0443\u043c\u043e\u0432\u0443\u0432\u0430\u043d\u043d\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 \u0432\u0435\u043a\u0442\u043e\u0440:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#definevector\n<\/span>x &lt;- c(3, 4, 4, 5, 7, 8, 9, 12, 13, 13, 15, 19, 21)\n\n<span style=\"color: #008080;\">#summarize values in vector\n<\/span>summary(x)\n\n   Min. 1st Qu. Median Mean 3rd Qu. Max. \n   3.00 5.00 9.00 10.23 13.00 21.00 \n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">\u0424\u0443\u043d\u043a\u0446\u0456\u044f <strong>summary()<\/strong> \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u043d\u043e \u043e\u0431\u0447\u0438\u0441\u043b\u044e\u0454 \u0442\u0430\u043a\u0456 \u043f\u0456\u0434\u0441\u0443\u043c\u043a\u043e\u0432\u0456 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u043d\u0456 \u0434\u0430\u043d\u0456 \u0434\u043b\u044f \u0432\u0435\u043a\u0442\u043e\u0440\u0430:<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\">Min: \u043c\u0456\u043d\u0456\u043c\u0430\u043b\u044c\u043d\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f<\/span><\/li>\n<li> <span style=\"color: #000000;\">1st Qu: \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f 1-\u0433\u043e \u043a\u0432\u0430\u0440\u0442\u0438\u043b\u044f (25-\u0439 \u043f\u0440\u043e\u0446\u0435\u043d\u0442\u0438\u043b\u044c)<\/span><\/li>\n<li> <span style=\"color: #000000;\">\u041c\u0435\u0434\u0456\u0430\u043d\u0430: \u0441\u0435\u0440\u0435\u0434\u043d\u0454 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f<\/span><\/li>\n<li> <span style=\"color: #000000;\">3rd Qu: \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f 3-\u0433\u043e \u043a\u0432\u0430\u0440\u0442\u0438\u043b\u044f (75-\u0439 \u043f\u0440\u043e\u0446\u0435\u043d\u0442\u0438\u043b\u044c)<\/span><\/li>\n<li> <span style=\"color: #000000;\">Max: \u043c\u0430\u043a\u0441\u0438\u043c\u0430\u043b\u044c\u043d\u0435 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f<\/span><\/li>\n<\/ul>\n<p> <span style=\"color: #000000;\">\u0417\u0430\u0443\u0432\u0430\u0436\u0442\u0435, \u0449\u043e \u044f\u043a\u0449\u043e \u0443 \u0432\u0435\u043a\u0442\u043e\u0440\u0456 \u0454 \u0432\u0456\u0434\u0441\u0443\u0442\u043d\u0456 \u0437\u043d\u0430\u0447\u0435\u043d\u043d\u044f (NA), \u0444\u0443\u043d\u043a\u0446\u0456\u044f <strong>summary()<\/strong> \u0430\u0432\u0442\u043e\u043c\u0430\u0442\u0438\u0447\u043d\u043e \u0432\u0438\u043a\u043b\u044e\u0447\u0438\u0442\u044c \u0457\u0445 \u043f\u0440\u0438 \u043e\u0431\u0447\u0438\u0441\u043b\u0435\u043d\u043d\u0456 \u043f\u0456\u0434\u0441\u0443\u043c\u043a\u043e\u0432\u043e\u0457 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#definevector\n<\/span>x &lt;- c(3, 4, 4, 5, 7, 8, 9, 12, 13, 13, 15, 19, 21, NA, NA)\n\n<span style=\"color: #008080;\">#summarize values in vector\n<\/span>summary(x)\n\n   Min. 1st Qu. Median Mean 3rd Qu. Max. NA's \n   3.00 5.00 9.00 10.23 13.00 21.00 2<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 2: \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f summary() \u0456\u0437 Data Frame<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e <strong>summary()<\/strong> \u0434\u043b\u044f \u043f\u0456\u0434\u0441\u0443\u043c\u043e\u0432\u0443\u0432\u0430\u043d\u043d\u044f \u043a\u043e\u0436\u043d\u043e\u0433\u043e \u0441\u0442\u043e\u0432\u043f\u0446\u044f \u0443 \u0444\u0440\u0435\u0439\u043c\u0456 \u0434\u0430\u043d\u0438\u0445:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define data frame\n<\/span>df &lt;- data. <span style=\"color: #3366ff;\">frame<\/span> (team=c('A', 'B', 'C', 'D', 'E'),\n                 points=c(99, 90, 86, 88, 95),\n                 assists=c(33, 28, 31, 39, 34),\n                 rebounds=c(30, 28, 24, 24, 28))\n\n<span style=\"color: #008080;\">#summarize every column in data frame\n<\/span>summary(df)\n\n     team points assists rebounds   \n Length:5 Min. :86.0 Min. :28 Min. :24.0  \n Class:character 1st Qu.:88.0 1st Qu.:31 1st Qu.:24.0  \n Mode:character Median:90.0 Median:33 Median:28.0  \n                    Mean:91.6 Mean:33 Mean:26.8  \n                    3rd Qu.:95.0 3rd Qu.:34 3rd Qu.:28.0  \n                    Max. :99.0 Max. :39 Max. :30.0 \n<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 3: \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f summary() \u0456\u0437 \u043f\u0435\u0432\u043d\u0438\u043c\u0438 \u0441\u0442\u043e\u0432\u043f\u0446\u044f\u043c\u0438 \u0444\u0440\u0435\u0439\u043c\u0443 \u0434\u0430\u043d\u0438\u0445<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e <strong>summary()<\/strong> \u0434\u043b\u044f \u043f\u0456\u0434\u0441\u0443\u043c\u043e\u0432\u0443\u0432\u0430\u043d\u043d\u044f \u043f\u0435\u0432\u043d\u0438\u0445 \u0441\u0442\u043e\u0432\u043f\u0446\u0456\u0432 \u0443 \u043a\u0430\u0434\u0440\u0456 \u0434\u0430\u043d\u0438\u0445:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define data frame\n<\/span>df &lt;- data. <span style=\"color: #3366ff;\">frame<\/span> (team=c('A', 'B', 'C', 'D', 'E'),\n                 points=c(99, 90, 86, 88, 95),\n                 assists=c(33, 28, 31, 39, 34),\n                 rebounds=c(30, 28, 24, 24, 28))\n\n<span style=\"color: #008080;\">#summarize every column in data frame\n<\/span>summary(df[c(' <span style=\"color: #ff0000;\">points<\/span> ', ' <span style=\"color: #ff0000;\">rebounds<\/span> ')])\n\n     rebound points   \n Min. :86.0 Min. :24.0  \n 1st Qu.:88.0 1st Qu.:24.0  \n Median:90.0 Median:28.0  \n Mean:91.6 Mean:26.8  \n 3rd Qu.:95.0 3rd Qu.:28.0  \n Max. :99.0 Max. :30.0<\/strong><\/pre>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 4: \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f summary() \u0456\u0437 \u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0439\u043d\u043e\u044e \u043c\u043e\u0434\u0435\u043b\u043b\u044e<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u0423 \u043d\u0430\u0441\u0442\u0443\u043f\u043d\u043e\u043c\u0443 \u043a\u043e\u0434\u0456 \u043f\u043e\u043a\u0430\u0437\u0430\u043d\u043e, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e <strong>summary()<\/strong> \u0434\u043b\u044f \u0443\u0437\u0430\u0433\u0430\u043b\u044c\u043d\u0435\u043d\u043d\u044f \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0456\u0432 \u043c\u043e\u0434\u0435\u043b\u0456 \u043b\u0456\u043d\u0456\u0439\u043d\u043e\u0457 \u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0457:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define data\n<\/span>df &lt;- data. <span style=\"color: #3366ff;\">frame<\/span> (y=c(99, 90, 86, 88, 95, 99, 91),\n                 x=c(33, 28, 31, 39, 34, 35, 36))\n\n<span style=\"color: #008080;\">#fit linear regression model\n<\/span>model &lt;- lm(y~x, data=df)\n\n<span style=\"color: #008080;\">#summarize model fit\n<\/span>summary(model)\n\nCall:\nlm(formula = y ~ x, data = df)\n\nResiduals:\n     1 2 3 4 5 6 7 \n 6,515 -1,879 -6,242 -5,212 2,394 6,273 -1,848 \n\nCoefficients:\n            Estimate Std. Error t value Pr(&gt;|t|)  \n(Intercept) 88.4848 22.1050 4.003 0.0103 *\nx 0.1212 0.6526 0.186 0.8599  \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n\nResidual standard error: 5.668 on 5 degrees of freedom\nMultiple R-squared: 0.006853, Adjusted R-squared: -0.1918 \nF-statistic: 0.0345 on 1 and 5 DF, p-value: 0.8599\n<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u041f\u043e\u0432\u2019\u044f\u0437\u0430\u043d\u0435:<\/strong><\/span> <a href=\"https:\/\/statorials.org\/uk\/\u0456\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0443\u0432\u0430\u0442\u0438-\u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442-\u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0456-\u0432-r\/\" target=\"_blank\" rel=\"noopener\">\u044f\u043a \u0456\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0443\u0432\u0430\u0442\u0438 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442 \u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0457 \u0432 R<\/a><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u041f\u0440\u0438\u043a\u043b\u0430\u0434 5: \u0412\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f summary() \u0456\u0437 \u043c\u043e\u0434\u0435\u043b\u043b\u044e ANOVA<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e <strong>summary()<\/strong> \u0434\u043b\u044f \u043f\u0456\u0434\u0441\u0443\u043c\u043e\u0432\u0443\u0432\u0430\u043d\u043d\u044f \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0456\u0432 \u043c\u043e\u0434\u0435\u043b\u0456 ANOVA \u0432 R:<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#make this example reproducible\n<\/span>set. <span style=\"color: #3366ff;\">seeds<\/span> (0)\n\n<span style=\"color: #008080;\">#create data frame\n<\/span>data &lt;- data. <span style=\"color: #3366ff;\">frame<\/span> (program = <span style=\"color: #3366ff;\">rep<\/span> (c(\"A\", \"B\", \"C\"), <span style=\"color: #3366ff;\">each<\/span> = <span style=\"color: #008000;\">30<\/span> ),\n                   weight_loss = c(runif(30, 0, 3),\n                                   runif(30, 0, 5),\n                                   runif(30, 1, 7)))\n\n<span style=\"color: #008080;\">#fit ANOVA model\n<\/span>model &lt;- aov(weight_loss ~ program, data = data)\n\n<span style=\"color: #008080;\">#summarize model fit\n<\/span>summary(model)\n\n            Df Sum Sq Mean Sq F value Pr(&gt;F)    \nprogram 2 98.93 49.46 30.83 7.55e-11 ***\nResiduals 87 139.57 1.60                     \n---\nSignificant. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1<\/strong><\/pre>\n<p> <span style=\"color: #000000;\"><strong>\u041f\u043e\u0432\u2019\u044f\u0437\u0430\u043d\u0435:<\/strong><\/span> <a href=\"https:\/\/statorials.org\/uk\/\u0456\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0443\u0432\u0430\u0442\u0438-\u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0438-lanova-\u0432-r\/\" target=\"_blank\" rel=\"noopener\">\u044f\u043a \u0456\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0443\u0432\u0430\u0442\u0438 \u0440\u0435\u0437\u0443\u043b\u044c\u0442\u0430\u0442\u0438 ANOVA \u0443 R<\/a><\/p>\n<h3> <span style=\"color: #000000;\"><strong>\u0414\u043e\u0434\u0430\u0442\u043a\u043e\u0432\u0456 \u0440\u0435\u0441\u0443\u0440\u0441\u0438<\/strong><\/span><\/h3>\n<p> <span style=\"color: #000000;\">\u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043d\u0430\u0432\u0447\u0430\u043b\u044c\u043d\u0456 \u043f\u043e\u0441\u0456\u0431\u043d\u0438\u043a\u0438 \u043f\u0440\u043e\u043f\u043e\u043d\u0443\u044e\u0442\u044c \u0431\u0456\u043b\u044c\u0448\u0435 \u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0456\u0457 \u043f\u0440\u043e \u043e\u0431\u0447\u0438\u0441\u043b\u0435\u043d\u043d\u044f \u043f\u0456\u0434\u0441\u0443\u043c\u043a\u043e\u0432\u043e\u0457 \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u043a\u0438 \u0432 R:<\/span><\/p>\n<p> <a href=\"https:\/\/statorials.org\/uk\/\u043f\u044f\u0442\u044c-\u0447\u0438\u0441\u0435\u043b,-\u0443\u0437\u0430\u0433\u0430\u043b\u044c\u043d\u0435\u043d\u0438\u0445-\u0443-r\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u043e\u0431\u0447\u0438\u0441\u043b\u0438\u0442\u0438 \u043f\u0456\u0434\u0441\u0443\u043c\u043e\u043a \u043f&#8217;\u044f\u0442\u0438 \u0447\u0438\u0441\u0435\u043b \u0443 R<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u0437\u0432\u0435\u0434\u0435\u043d\u0430-\u0442\u0430\u0431\u043b\u0438\u0446\u044f-\u0432-\u0440\/\" target=\"_blank\" rel=\"noopener\">\u041d\u0430\u0439\u043f\u0440\u043e\u0441\u0442\u0456\u0448\u0438\u0439 \u0441\u043f\u043e\u0441\u0456\u0431 \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0437\u0432\u0435\u0434\u0435\u043d\u0456 \u0442\u0430\u0431\u043b\u0438\u0446\u0456 \u0432 R<\/a><br \/> <a href=\"https:\/\/statorials.org\/uk\/\u0442\u0430\u0431\u043b\u0438\u0446\u044f-\u0432\u0456\u0434\u043d\u043e\u0441\u043d\u043e\u0456-\u0447\u0430\u0441\u0442\u043e\u0442\u0438-\u0432-r\/\" target=\"_blank\" rel=\"noopener\">\u042f\u043a \u0441\u0442\u0432\u043e\u0440\u0438\u0442\u0438 \u0442\u0430\u0431\u043b\u0438\u0446\u0456 \u0432\u0456\u0434\u043d\u043e\u0441\u043d\u043e\u0457 \u0447\u0430\u0441\u0442\u043e\u0442\u0438 \u0432 R<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u0424\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0443 R \u043c\u043e\u0436\u043d\u0430 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0434\u043b\u044f \u0448\u0432\u0438\u0434\u043a\u043e\u0433\u043e \u043f\u0456\u0434\u0441\u0443\u043c\u043e\u0432\u0443\u0432\u0430\u043d\u043d\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 \u0432\u0435\u043a\u0442\u043e\u0440\u0456, \u043a\u0430\u0434\u0440\u0456 \u0434\u0430\u043d\u0438\u0445, \u043c\u043e\u0434\u0435\u043b\u0456 \u0440\u0435\u0433\u0440\u0435\u0441\u0456\u0457 \u0430\u0431\u043e \u043c\u043e\u0434\u0435\u043b\u0456 ANOVA \u0432 R. \u0426\u0435\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0454 \u0442\u0430\u043a\u0438\u0439 \u0431\u0430\u0437\u043e\u0432\u0438\u0439 \u0441\u0438\u043d\u0442\u0430\u043a\u0441\u0438\u0441: summary(data) \u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0456 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0438 \u043f\u043e\u043a\u0430\u0437\u0443\u044e\u0442\u044c, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0446\u044e \u0444\u0443\u043d\u043a\u0446\u0456\u044e \u043d\u0430 \u043f\u0440\u0430\u043a\u0442\u0438\u0446\u0456. \u041f\u0440\u0438\u043a\u043b\u0430\u0434 1: \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f summary() \u0456\u0437 Vector \u041d\u0430\u0441\u0442\u0443\u043f\u043d\u0438\u0439 \u043a\u043e\u0434 \u043f\u043e\u043a\u0430\u0437\u0443\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0434\u043b\u044f \u043f\u0456\u0434\u0441\u0443\u043c\u043e\u0432\u0443\u0432\u0430\u043d\u043d\u044f \u0437\u043d\u0430\u0447\u0435\u043d\u044c \u0443 \u0432\u0435\u043a\u0442\u043e\u0440: [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0432 R (\u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438) - Statorials<\/title>\n<meta name=\"description\" content=\"\u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0443 R, \u0437 \u043a\u0456\u043b\u044c\u043a\u043e\u043c\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438.\" \/>\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\/uk\/\u043f\u0456\u0434\u0441\u0443\u043c\u043a\u043e\u0432\u0430-\u0444\u0443\u043d\u043a\u0446\u0456\u044f-\u0432-r\/\" \/>\n<meta property=\"og:locale\" content=\"uk_UA\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0432 R (\u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438) - Statorials\" \/>\n<meta property=\"og:description\" content=\"\u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0443 R, \u0437 \u043a\u0456\u043b\u044c\u043a\u043e\u043c\u0430 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/statorials.org\/uk\/\u043f\u0456\u0434\u0441\u0443\u043c\u043a\u043e\u0432\u0430-\u0444\u0443\u043d\u043a\u0446\u0456\u044f-\u0432-r\/\" \/>\n<meta property=\"og:site_name\" content=\"Statorials\" \/>\n<meta property=\"article:published_time\" content=\"2023-07-23T18:03:32+00:00\" \/>\n<meta name=\"author\" content=\"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u041d\u0430\u043f\u0438\u0441\u0430\u043d\u043e\" \/>\n\t<meta name=\"twitter:data1\" content=\"\u0420\u0435\u0434\u0430\u043a\u0446\u0456\u044f\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u041f\u0440\u0438\u0431\u043b. \u0447\u0430\u0441 \u0447\u0438\u0442\u0430\u043d\u043d\u044f\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 \u0445\u0432\u0438\u043b\u0438\u043d\u0438\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/statorials.org\/uk\/%d0%bf%d1%96%d0%b4%d1%81%d1%83%d0%bc%d0%ba%d0%be%d0%b2%d0%b0-%d1%84%d1%83%d0%bd%d0%ba%d1%86%d1%96%d1%8f-%d0%b2-r\/\",\"url\":\"https:\/\/statorials.org\/uk\/%d0%bf%d1%96%d0%b4%d1%81%d1%83%d0%bc%d0%ba%d0%be%d0%b2%d0%b0-%d1%84%d1%83%d0%bd%d0%ba%d1%86%d1%96%d1%8f-%d0%b2-r\/\",\"name\":\"\u042f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0432 R (\u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438) - Statorials\",\"isPartOf\":{\"@id\":\"https:\/\/statorials.org\/uk\/#website\"},\"datePublished\":\"2023-07-23T18:03:32+00:00\",\"dateModified\":\"2023-07-23T18:03:32+00:00\",\"author\":{\"@id\":\"https:\/\/statorials.org\/uk\/#\/schema\/person\/2affa1a5da08a4b61ab4becd078c191a\"},\"description\":\"\u0426\u0435\u0439 \u043f\u0456\u0434\u0440\u0443\u0447\u043d\u0438\u043a \u043f\u043e\u044f\u0441\u043d\u044e\u0454, \u044f\u043a \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u043e\u0432\u0443\u0432\u0430\u0442\u0438 \u0444\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0443 R, \u0437 \u043a\u0456\u043b\u044c\u043a\u043e\u043c\u0430 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\u0444\u0443\u043d\u043a\u0446\u0456\u044e summary() \u0443 r (\u0437 \u043f\u0440\u0438\u043a\u043b\u0430\u0434\u0430\u043c\u0438)\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/statorials.org\/uk\/#website\",\"url\":\"https:\/\/statorials.org\/uk\/\",\"name\":\"Statorials\",\"description\":\"\u0412\u0430\u0448 \u043f\u0443\u0442\u0456\u0432\u043d\u0438\u043a \u0434\u043e \u0441\u0442\u0430\u0442\u0438\u0441\u0442\u0438\u0447\u043d\u043e\u0457 \u043a\u043e\u043c\u043f\u0435\u0442\u0435\u043d\u0442\u043d\u043e\u0441\u0442\u0456!\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/statorials.org\/uk\/?s={search_term_string}\"},\"query-input\":\"required 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