{"id":487,"date":"2023-07-29T17:59:32","date_gmt":"2023-07-29T17:59:32","guid":{"rendered":"https:\/\/statorials.org\/my\/%e1%80%a1%e1%80%9e%e1%80%80%e1%80%ba%e1%80%a1%e1%80%9b%e1%80%bd%e1%80%9a%e1%80%ba%e1%80%95%e1%80%ad%e1%80%9b%e1%80%99%e1%80%85%e1%80%ba-r\/"},"modified":"2023-07-29T17:59:32","modified_gmt":"2023-07-29T17:59:32","slug":"%e1%80%a1%e1%80%9e%e1%80%80%e1%80%ba%e1%80%a1%e1%80%9b%e1%80%bd%e1%80%9a%e1%80%ba%e1%80%95%e1%80%ad%e1%80%9b%e1%80%99%e1%80%85%e1%80%ba-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/my\/%e1%80%a1%e1%80%9e%e1%80%80%e1%80%ba%e1%80%a1%e1%80%9b%e1%80%bd%e1%80%9a%e1%80%ba%e1%80%95%e1%80%ad%e1%80%9b%e1%80%99%e1%80%85%e1%80%ba-r\/","title":{"rendered":"R \u1010\u103d\u1004\u103a \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038"},"content":{"rendered":"

<\/p>\n

\n

\u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a<\/strong> \u101e\u100a\u103a \u1015\u1031\u1038\u1011\u102c\u1038\u101e\u1031\u102c\u101c\u1030\u1026\u1038\u101b\u1031\u104f \u1021\u101e\u1000\u103a\u1014\u103e\u1004\u1037\u103a \u101c\u102d\u1004\u103a\u1001\u103d\u1032\u101d\u1031\u1019\u103e\u102f\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u1037\u103a \u1002\u101b\u1015\u103a\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b \u1024\u101e\u100a\u103a\u1019\u103e\u102c \u101c\u1030\u1026\u1038\u101b\u1031\u104f\u1016\u103d\u1032\u1037\u1005\u100a\u103a\u1038\u1019\u103e\u102f\u1014\u103e\u1004\u1037\u103a \u101c\u1000\u103a\u101b\u103e\u102d\u101c\u1030\u1026\u1038\u101b\u1031\u1010\u102d\u102f\u1038\u1014\u103e\u102f\u1014\u103a\u1038\u1000\u102d\u102f \u1021\u101c\u103d\u101a\u103a\u1010\u1000\u1030\u1014\u102c\u1038\u101c\u100a\u103a\u101b\u1014\u103a \u1021\u101e\u102f\u1036\u1038\u101d\u1004\u103a\u101e\u1031\u102c\u1007\u101a\u102c\u1038\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b<\/span><\/p>\n

\u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1010\u103d\u1004\u103a \u1005\u1010\u102f\u1002\u1036\u1015\u102f\u1036\u101e\u100f\u1039\u100d\u102c\u1014\u103a\u101b\u103e\u102d\u1015\u102b\u1000\u104a \u101c\u1030\u1026\u1038\u101b\u1031\u101e\u100a\u103a \u1014\u103e\u1031\u1038\u1000\u103d\u1031\u1038\u101e\u1031\u102c\u1014\u103e\u102f\u1014\u103a\u1038\u1016\u103c\u1004\u1037\u103a \u1000\u103c\u102e\u1038\u1011\u103d\u102c\u1038\u1014\u1031\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u100a\u103d\u103e\u1014\u103a\u1015\u103c\u1015\u102b\u101e\u100a\u103a\u104b \u1021\u1014\u102e\u1038\u1005\u1015\u103a\u1006\u102f\u1036\u1038 \u1021\u101b\u103d\u101a\u103a\u1010\u1030 \u1019\u103b\u102d\u102f\u1038\u1006\u1000\u103a\u101e\u1005\u103a\u1019\u103b\u102c\u1038\u1016\u103c\u1004\u1037\u103a \u1021\u1005\u102c\u1038\u1011\u102d\u102f\u1038\u101e\u100a\u103a\u104b<\/span><\/p>\n

\u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u101e\u100a\u103a \u1015\u102d\u101b\u1019\u1005\u103a\u1010\u1005\u103a\u1001\u102f\u1000\u1032\u1037\u101e\u102d\u102f\u1037 \u1015\u102f\u1036\u101e\u100f\u1039\u100d\u102c\u1014\u103a\u1016\u103c\u1005\u103a\u1015\u102b\u1000\u104a \u101c\u1030\u1026\u1038\u101b\u1031\u101e\u100a\u103a \u1015\u102d\u102f\u1019\u102d\u102f\u1019\u103c\u1014\u103a\u1006\u1014\u103a\u1005\u103d\u102c \u1000\u103c\u102e\u1038\u1011\u103d\u102c\u1038\u101c\u102c\u1014\u1031\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u100a\u103d\u103e\u1014\u103a\u1015\u103c\u1015\u102b\u101e\u100a\u103a\u104b \u1019\u103b\u102d\u102f\u1038\u1006\u1000\u103a\u101f\u1031\u102c\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1019\u103b\u102d\u102f\u1038\u1006\u1000\u103a\u101e\u1005\u103a\u104a \u1000\u103c\u102e\u1038\u1019\u102c\u1038\u101e\u1031\u102c \u1019\u103b\u102d\u102f\u1038\u1006\u1000\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u103d\u1031\u1038\u1011\u102f\u1010\u103a\u1015\u1031\u1038\u101e\u100a\u103a\u104b<\/span><\/p>\n

\u1002\u101b\u1015\u103a\u1010\u103d\u1004\u103a \u1000\u103b\u102c\u1038\u104a\u1019\u1000\u102d\u102f \u1018\u101a\u103a\u100a\u102c\u1014\u103e\u1004\u1037\u103a \u1018\u101a\u103a\u1018\u1000\u103a\u1001\u103c\u1019\u103a\u1038\u1010\u103d\u1004\u103a \u1015\u103c\u1011\u102c\u1038\u1015\u103c\u102e\u1038\u104a \u1021\u101e\u1000\u103a\u1000\u102d\u102f y \u101d\u1004\u103a\u101b\u102d\u102f\u1038\u1015\u1031\u102b\u103a\u1010\u103d\u1004\u103a \u1015\u103c\u1011\u102c\u1038\u1015\u103c\u102e\u1038 \u101c\u1030\u1026\u1038\u101b\u1031 \u101b\u102c\u1001\u102d\u102f\u1004\u103a\u1014\u103e\u102f\u1014\u103a\u1038 \u101e\u102d\u102f\u1037\u1019\u101f\u102f\u1010\u103a \u1015\u1019\u102c\u100f\u1000\u102d\u102f x-axis \u1010\u103d\u1004\u103a \u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b<\/span><\/p>\n

\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a R \u1010\u103d\u1004\u103a \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1010\u1005\u103a\u1001\u102f\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b<\/span><\/p>\n

R \u1010\u103d\u1004\u103a \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1010\u1005\u103a\u1001\u102f\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1015\u102b\u104b<\/strong><\/span><\/h3>\n

\u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u1010\u103d\u1004\u103a \u1021\u101e\u1000\u103a (0 \u1019\u103e 100 \u1014\u103e\u1005\u103a) \u1014\u103e\u1004\u1037\u103a \u101c\u102d\u1004\u103a (M = “ Male” , F = “ Female” ) \u1010\u102d\u102f\u1037\u1000\u102d\u102f \u1021\u1001\u103c\u1031\u1001\u1036\u104d \u101c\u1030\u1026\u1038\u101b\u1031\u104f \u101b\u102c\u1001\u102d\u102f\u1004\u103a\u1014\u103e\u102f\u1014\u103a\u1038\u1016\u103d\u1032\u1037\u1005\u100a\u103a\u1038\u1015\u102f\u1036\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u1037\u103a \u1021\u1031\u102c\u1000\u103a\u1015\u102b\u1012\u1031\u1010\u102c\u1021\u1005\u102f\u1036\u101b\u103e\u102d\u101e\u100a\u103a\u1006\u102d\u102f\u1015\u102b\u1005\u102d\u102f\u1037\u104b<\/span><\/p>\n

 #make this example reproducible<\/span>\nset.seed(1)\n\n#create data frame\n<\/span>data <- data.frame(age = rep(1:100, 2), gender = rep(c(\"M\", \"F\"), each = 100))\n\n#add variable population\n<\/span>data$population <- 1\/sqrt(data$age) * runif(200, 10000, 15000)\n\n#convert population variable to percentage\n<\/span>data$population <- data$population \/ sum(data$population) * 100\n\n#view first six rows of dataset\n<\/span>head(data)\n\n# age gender population\n#1 1M 2.424362\n#2 2M 1.794957\n#3 3M 1.589594\n#4 4M 1.556063\n#5 5M 1.053662\n#6 6M 1.266231\n<\/strong><\/pre>\n
 ggplot2<\/strong> \u1005\u102c\u1000\u103c\u100a\u1037\u103a\u1010\u102d\u102f\u1000\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d \u1024\u1012\u1031\u1010\u102c\u1021\u1010\u103d\u1032\u1021\u1010\u103d\u1000\u103a \u1021\u1001\u103c\u1031\u1001\u1036\u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1010\u1005\u103a\u1001\u102f\u1000\u102d\u102f \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037 \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span><\/p>\n
 #load ggplot2\n<\/em><\/span>library(ggplot2)\n\n#create population pyramid<\/span>\nggplot(data, aes(x = age, fill = gender,\n                 y = ifelse(test = gender == \"M\",\n                            yes = -population, no = population))) + \n  geom_bar(stat = \"identity\") +\n  scale_y_continuous(labels = abs, limits = max(data$population) * c(-1,1)) +\n  coordinate_flip()<\/strong><\/pre>\n
 \u1001\u1031\u102b\u1004\u103a\u1038\u1005\u1009\u103a\u1019\u103b\u102c\u1038\u1014\u103e\u1004\u1037\u103a \u1010\u1002\u103a\u1019\u103b\u102c\u1038\u1011\u100a\u1037\u103a\u1001\u103c\u1004\u103a\u1038\u104b<\/strong><\/h3>\n
 labs()<\/strong> \u1021\u1000\u103c\u1031\u102c\u1004\u103a\u1038\u1015\u103c\u1001\u103b\u1000\u103a\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1010\u103d\u1004\u103a \u1001\u1031\u102b\u1004\u103a\u1038\u1005\u1009\u103a\u1019\u103b\u102c\u1038\u1014\u103e\u1004\u1037\u103a \u101d\u1004\u103a\u101b\u102d\u102f\u1038\u1021\u100a\u103d\u103e\u1014\u103a\u1038\u1019\u103b\u102c\u1038 \u1014\u103e\u1005\u103a\u1001\u102f\u101c\u102f\u1036\u1038\u1000\u102d\u102f \u1011\u100a\u1037\u103a\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span><\/p>\n
 ggplot(data, aes(x = age, fill = gender,\n                 y = ifelse(test = gender == \"M\",\n                            yes = -population, no = population))) + \n  geom_bar(stat = \"identity\") +\n  scale_y_continuous(labels = abs, limits = max(data$population) * c(-1,1)) +\n  labs(title = \"Population Pyramid\", x = \"Age\", y = \"Percent of population\")<\/span> +\n  coordinate_flip()<\/strong><\/pre>\n
 \u1021\u101b\u1031\u102c\u1004\u103a\u1015\u103c\u1031\u102c\u1004\u103a\u1038\u1015\u102b\u104b<\/strong><\/span><\/h3>\n
 scale_color_manual()<\/strong> \u1021\u1004\u103c\u1004\u103a\u1038\u1021\u1001\u102f\u1036\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d \u101c\u102d\u1004\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1000\u102d\u102f\u101a\u103a\u1005\u102c\u1038\u1015\u103c\u102f\u101b\u1014\u103a \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101e\u100a\u1037\u103a \u1021\u101b\u1031\u102c\u1004\u103a\u1014\u103e\u1005\u103a\u1019\u103b\u102d\u102f\u1038\u1000\u102d\u102f \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037 \u1015\u103c\u1031\u102c\u1004\u103a\u1038\u101c\u1032\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a-<\/span><\/p>\n
 ggplot(data, aes(x = age, fill = gender,\n                 y = ifelse(test = gender == \"M\",\n                            yes = -population, no = population))) + \n  geom_bar(stat = \"identity\") +\n  scale_y_continuous(labels = abs, limits = max(data$population) * c(-1,1)) +\n  labs(title = \"Population Pyramid\", x = \"Age\", y = \"Percent of population\") +\n  scale_color_manual(values = c(\"pink\", \"steelblue\"),<\/span>\naesthetics = c(\"color\", \"fill\"))<\/span> +\n  coordinate_flip()<\/strong><\/pre>\n
 \u1001\u1031\u1010\u103a\u1015\u1031\u102b\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u1005\u103d\u102c \u1015\u102d\u101b\u1019\u1005\u103a\u1019\u103b\u102c\u1038<\/strong><\/span><\/h2>\n
 facet_wrap()<\/strong> \u1021\u1004\u103c\u1004\u103a\u1038\u1021\u1001\u102f\u1036\u1000\u102d\u102f \u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u104d \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1021\u1019\u103b\u102c\u1038\u1021\u1015\u103c\u102c\u1038\u1000\u102d\u102f \u1010\u103d\u1032\u1006\u103d\u1032\u101b\u1014\u103a\u101c\u100a\u103a\u1038 \u1016\u103c\u1005\u103a\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b \u1025\u1015\u1019\u102c\u1021\u102c\u1038\u1016\u103c\u1004\u1037\u103a\u104a \u1000\u103b\u103d\u1014\u103a\u102f\u1015\u103a\u1010\u102d\u102f\u1037\u1010\u103d\u1004\u103a \u1014\u102d\u102f\u1004\u103a\u1004\u1036 A\u104a B<\/em> \u1014\u103e\u1004\u1037\u103a C<\/em> \u1021\u1010\u103d\u1000\u103a \u101c\u1030\u1026\u1038\u101b\u1031\u1012\u1031\u1010\u102c \u101b\u103e\u102d\u101e\u100a\u103a\u1006\u102d\u102f\u1015\u102b\u1005\u102d\u102f\u1037\u104b \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b \u1000\u102f\u1012\u103a\u101e\u100a\u103a \u1014\u102d\u102f\u1004\u103a\u1004\u1036\u1010\u1005\u103a\u1001\u102f\u1005\u102e\u1021\u1010\u103d\u1000\u103a \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1010\u1005\u103a\u1001\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1015\u102f\u1036\u1000\u102d\u102f \u101e\u101b\u102f\u1015\u103a\u1016\u1031\u102c\u103a\u101e\u100a\u103a-<\/span><\/p>\n
 #make this example reproducible<\/span>\nset.seed(1)\n\n#create data frame\n<\/span>data_multiple <- data.frame(age = rep(1:100, 6),\n                   gender = rep(c(\"M\", \"F\"), each = 300),\n                   country = rep(c(\"A\", \"B\", \"C\"), each = 100, times = 2))\n\n#add variable population\n<\/span>data_multiple$population <- round(1\/sqrt(data_multiple$age)*runif(200, 10000, 15000), 0)\n\n#view first six rows of dataset\n<\/span>head(data_multiple)\n\n# age gender country population\n#1 1 MA 11328\n#2 2 MA 8387\n#3 3 MA 7427\n#4 4 MA 7271\n#5 5 MA 4923\n#6 6 MA 5916\n\n#create one population pyramid per country\n<\/span>ggplot(data_multiple, aes(x = age, fill = gender,\n                          y = ifelse(test = gender == \"M\",\n                                     yes = -population, no = population))) + \n  geom_bar(stat = \"identity\") +\n  scale_y_continuous(labels = abs, limits = max(data_multiple$population) * c(-1,1)) +\n  labs(y = \"Population Amount\") + \n  coordinate_flip() +\n  facet_wrap(~country) +<\/span>\ntheme(axis.text.x = element_text(angle = 90, hjust = 1))<\/span> #rotate x-axis labels<\/span><\/span><\/strong><\/pre>\n
 \u1021\u1015\u103c\u1004\u103a\u1021\u1006\u1004\u103a\u1000\u102d\u102f \u1015\u103c\u1031\u102c\u1004\u103a\u1038\u1015\u102b\u104b<\/strong><\/span><\/h2>\n
 \u1014\u1031\u102c\u1000\u103a\u1006\u102f\u1036\u1038\u1010\u103d\u1004\u103a\u104a \u1002\u101b\u1015\u103a\u1016\u1005\u103a\u104f\u1021\u1001\u1004\u103a\u1038\u1021\u1000\u103b\u1004\u103a\u1038\u1000\u102d\u102f\u1015\u103c\u1031\u102c\u1004\u103a\u1038\u101c\u1032\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b \u1025\u1015\u1019\u102c\u1021\u102c\u1038\u1016\u103c\u1004\u1037\u103a\u104a \u1021\u1031\u102c\u1000\u103a\u1016\u1031\u102c\u103a\u1015\u103c\u1015\u102b\u1000\u102f\u1012\u103a\u101e\u100a\u103a \u1002\u101b\u1015\u103a\u1016\u1005\u103a\u1000\u102d\u102f \u1015\u102d\u102f\u1019\u102d\u102f\u101e\u1031\u1038\u1004\u101a\u103a\u101e\u1031\u102c\u1015\u102f\u1036\u1016\u103c\u1005\u103a\u1021\u1031\u102c\u1004\u103a\u1015\u103c\u102f\u101c\u102f\u1015\u103a\u101b\u1014\u103a theme_classic()<\/strong> \u1000\u102d\u102f\u1021\u101e\u102f\u1036\u1038\u1015\u103c\u102f\u101e\u100a\u103a-<\/span><\/p>\n
 ggplot(data_multiple, aes(x = age, fill = gender,\n                          y = ifelse(test = gender == \"M\",\n                                     yes = -population, no = population))) + \n  geom_bar(stat = \"identity\") +\n  scale_y_continuous(labels = abs, limits = max(data_multiple$population) * c(-1,1)) +\n  labs(y = \"Population Amount\") + \n  coordinate_flip() +\n  facet_wrap(~country) +<\/span>\ntheme_classic()<\/span> + \n  theme(axis.text.x = element_text(angle = 90, hjust = 1))\n<\/strong><\/pre>\n
 \u101e\u102d\u102f\u1037\u1019\u101f\u102f\u1010\u103a \u1005\u102d\u1010\u103a\u1000\u103c\u102d\u102f\u1000\u103a ggthemes \u1000\u102d\u102f\u101e\u102f\u1036\u1038\u1014\u102d\u102f\u1004\u103a\u101e\u100a\u103a\u104b ggthemes \u104f\u1005\u102c\u101b\u1004\u103a\u1038\u1021\u1015\u103c\u100a\u1037\u103a\u1021\u1005\u102f\u1036\u1021\u1010\u103d\u1000\u103a\u104a<\/span> \u1005\u102c\u101b\u103d\u1000\u103a\u1005\u102c\u1010\u1019\u103a\u1038\u1005\u102c\u1019\u103b\u1000\u103a\u1014\u103e\u102c\u1000\u102d\u102f<\/a> \u1000\u103c\u100a\u1037\u103a\u1015\u102b \u104b<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
\u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a \u101e\u100a\u103a \u1015\u1031\u1038\u1011\u102c\u1038\u101e\u1031\u102c\u101c\u1030\u1026\u1038\u101b\u1031\u104f \u1021\u101e\u1000\u103a\u1014\u103e\u1004\u1037\u103a \u101c\u102d\u1004\u103a\u1001\u103d\u1032\u101d\u1031\u1019\u103e\u102f\u1000\u102d\u102f \u1015\u103c\u101e\u101e\u100a\u1037\u103a \u1002\u101b\u1015\u103a\u1010\u1005\u103a\u1001\u102f\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b \u1024\u101e\u100a\u103a\u1019\u103e\u102c \u101c\u1030\u1026\u1038\u101b\u1031\u104f\u1016\u103d\u1032\u1037\u1005\u100a\u103a\u1038\u1019\u103e\u102f\u1014\u103e\u1004\u1037\u103a \u101c\u1000\u103a\u101b\u103e\u102d\u101c\u1030\u1026\u1038\u101b\u1031\u1010\u102d\u102f\u1038\u1014\u103e\u102f\u1014\u103a\u1038\u1000\u102d\u102f \u1021\u101c\u103d\u101a\u103a\u1010\u1000\u1030\u1014\u102c\u1038\u101c\u100a\u103a\u101b\u1014\u103a \u1021\u101e\u102f\u1036\u1038\u101d\u1004\u103a\u101e\u1031\u102c\u1007\u101a\u102c\u1038\u1016\u103c\u1005\u103a\u101e\u100a\u103a\u104b \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1010\u103d\u1004\u103a \u1005\u1010\u102f\u1002\u1036\u1015\u102f\u1036\u101e\u100f\u1039\u100d\u102c\u1014\u103a\u101b\u103e\u102d\u1015\u102b\u1000\u104a \u101c\u1030\u1026\u1038\u101b\u1031\u101e\u100a\u103a \u1014\u103e\u1031\u1038\u1000\u103d\u1031\u1038\u101e\u1031\u102c\u1014\u103e\u102f\u1014\u103a\u1038\u1016\u103c\u1004\u1037\u103a \u1000\u103c\u102e\u1038\u1011\u103d\u102c\u1038\u1014\u1031\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u100a\u103d\u103e\u1014\u103a\u1015\u103c\u1015\u102b\u101e\u100a\u103a\u104b \u1021\u1014\u102e\u1038\u1005\u1015\u103a\u1006\u102f\u1036\u1038 \u1021\u101b\u103d\u101a\u103a\u1010\u1030 \u1019\u103b\u102d\u102f\u1038\u1006\u1000\u103a\u101e\u1005\u103a\u1019\u103b\u102c\u1038\u1016\u103c\u1004\u1037\u103a \u1021\u1005\u102c\u1038\u1011\u102d\u102f\u1038\u101e\u100a\u103a\u104b \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u101e\u100a\u103a \u1015\u102d\u101b\u1019\u1005\u103a\u1010\u1005\u103a\u1001\u102f\u1000\u1032\u1037\u101e\u102d\u102f\u1037 \u1015\u102f\u1036\u101e\u100f\u1039\u100d\u102c\u1014\u103a\u1016\u103c\u1005\u103a\u1015\u102b\u1000\u104a \u101c\u1030\u1026\u1038\u101b\u1031\u101e\u100a\u103a \u1015\u102d\u102f\u1019\u102d\u102f\u1019\u103c\u1014\u103a\u1006\u1014\u103a\u1005\u103d\u102c \u1000\u103c\u102e\u1038\u1011\u103d\u102c\u1038\u101c\u102c\u1014\u1031\u1000\u103c\u1031\u102c\u1004\u103a\u1038 \u100a\u103d\u103e\u1014\u103a\u1015\u103c\u1015\u102b\u101e\u100a\u103a\u104b \u1019\u103b\u102d\u102f\u1038\u1006\u1000\u103a\u101f\u1031\u102c\u1004\u103a\u1038\u1019\u103b\u102c\u1038\u101e\u100a\u103a \u1019\u103b\u102d\u102f\u1038\u1006\u1000\u103a\u101e\u1005\u103a\u104a \u1000\u103c\u102e\u1038\u1019\u102c\u1038\u101e\u1031\u102c \u1019\u103b\u102d\u102f\u1038\u1006\u1000\u103a\u1019\u103b\u102c\u1038\u1000\u102d\u102f \u1019\u103d\u1031\u1038\u1011\u102f\u1010\u103a\u1015\u1031\u1038\u101e\u100a\u103a\u104b \u1002\u101b\u1015\u103a\u1010\u103d\u1004\u103a \u1000\u103b\u102c\u1038\u104a\u1019\u1000\u102d\u102f \u1018\u101a\u103a\u100a\u102c\u1014\u103e\u1004\u1037\u103a \u1018\u101a\u103a\u1018\u1000\u103a\u1001\u103c\u1019\u103a\u1038\u1010\u103d\u1004\u103a \u1015\u103c\u1011\u102c\u1038\u1015\u103c\u102e\u1038\u104a \u1021\u101e\u1000\u103a\u1000\u102d\u102f y \u101d\u1004\u103a\u101b\u102d\u102f\u1038\u1015\u1031\u102b\u103a\u1010\u103d\u1004\u103a \u1015\u103c\u1011\u102c\u1038\u1015\u103c\u102e\u1038 \u101c\u1030\u1026\u1038\u101b\u1031 \u101b\u102c\u1001\u102d\u102f\u1004\u103a\u1014\u103e\u102f\u1014\u103a\u1038 \u101e\u102d\u102f\u1037\u1019\u101f\u102f\u1010\u103a \u1015\u1019\u102c\u100f\u1000\u102d\u102f x-axis \u1010\u103d\u1004\u103a \u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b \u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a R \u1010\u103d\u1004\u103a \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1010\u1005\u103a\u1001\u102f\u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038\u1000\u102d\u102f \u101b\u103e\u1004\u103a\u1038\u1015\u103c\u1011\u102c\u1038\u101e\u100a\u103a\u104b […]<\/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":"\nR - Statology \u1010\u103d\u1004\u103a \u101c\u1030\u1026\u1038\u101b\u1031\u1015\u102d\u101b\u1019\u1005\u103a\u1000\u102d\u102f \u1016\u1014\u103a\u1010\u102e\u1038\u1014\u100a\u103a\u1038<\/title>\n<meta name=\"description\" content=\"\u1024\u101e\u1004\u103a\u1001\u1014\u103a\u1038\u1005\u102c\u1010\u103d\u1004\u103a R \u1010\u103d\u1004\u103a 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