library(intsvy)
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 3.2.5
library(gridExtra)
## Warning: package 'gridExtra' was built under R version 3.2.5
library(grid)
library(car)
## Warning: package 'car' was built under R version 3.2.5
# Veri setlerini yeniden hesaplanmis ESCS degerleri ile birlestirme
# 2003
colnames(escs_2003)[1:3] <- c("CNT","SCHOOLID","STIDSTD")
pisa_2003_stu <- merge(pisa_2003_stu,escs_2003,by=c("CNT","SCHOOLID","STIDSTD") ,all=TRUE)
# 2006
levels(escs_2006$cnt)
## [1] "ARG" "AUS" "AUT" "BEL" "BGR" "BRA" "CAN" "CHE" "CHL" "COL" "CZE"
## [12] "DEU" "DNK" "ESP" "EST" "FIN" "FRA" "GBR" "GRC" "HKG" "HRV" "HUN"
## [23] "IDN" "IRL" "ISL" "ISR" "ITA" "JOR" "JPN" "KOR" "LTU" "LUX" "LVA"
## [34] "MAC" "MEX" "MNE" "NLD" "NOR" "NZL" "POL" "PRT" "QAT" "ROU" "RUS"
## [45] "SVK" "SVN" "SWE" "TAP" "THA" "TUN" "TUR" "URY" "USA"
levels(escs_2006$cnt) <- c("Argentina","Australia","Austria","Belgium","Bulgaria"
,"Brazil","Canada","Switzerland","Chile","Colombia",
"Czech Republic","Germany","Denmark","Spain","Estonia",
"Finland","France","United Kingdom","Greece",
"Hong Kong-China","Croatia","Hungary","Indonesia","Ireland",
"Iceland","Israel", "Italy","Jordan","Japan","Korea",
"Lithuania","Luxembourg","Latvia","Macao-China",
"Mexico","Montenegro","Netherlands","Norway","New Zealand",
"Poland","Portugal","Qatar","Romania","Russian Federation",
"Slovak Republic","Slovenia ","Sweden",
"Chinese Taipei","Thailand","Tunisia","Turkey","Uruguay",
"United States")
levels(escs_2006$cnt)
## [1] "Argentina" "Australia" "Austria"
## [4] "Belgium" "Bulgaria" "Brazil"
## [7] "Canada" "Switzerland" "Chile"
## [10] "Colombia" "Czech Republic" "Germany"
## [13] "Denmark" "Spain" "Estonia"
## [16] "Finland" "France" "United Kingdom"
## [19] "Greece" "Hong Kong-China" "Croatia"
## [22] "Hungary" "Indonesia" "Ireland"
## [25] "Iceland" "Israel" "Italy"
## [28] "Jordan" "Japan" "Korea"
## [31] "Lithuania" "Luxembourg" "Latvia"
## [34] "Macao-China" "Mexico" "Montenegro"
## [37] "Netherlands" "Norway" "New Zealand"
## [40] "Poland" "Portugal" "Qatar"
## [43] "Romania" "Russian Federation" "Slovak Republic"
## [46] "Slovenia " "Sweden" "Chinese Taipei"
## [49] "Thailand" "Tunisia" "Turkey"
## [52] "Uruguay" "United States"
colnames(escs_2006)[1:3] <- c("CNT","SCHOOLID","STIDSTD")
pisa_2006_stu <- merge(pisa_2006_stu,escs_2006,by=c("CNT","SCHOOLID","STIDSTD") ,all=TRUE)
# 2009
levels(escs_2009$cnt)
## [1] "ALB" "ARE" "ARG" "AUS" "AUT" "BEL" "BGR" "BRA" "CAN" "CHE" "CHL"
## [12] "COL" "CRI" "CZE" "DEU" "DNK" "ESP" "EST" "FIN" "FRA" "GBR" "GEO"
## [23] "GRC" "HKG" "HRV" "HUN" "IDN" "IRL" "ISL" "ISR" "ITA" "JOR" "JPN"
## [34] "KAZ" "KOR" "LTU" "LUX" "LVA" "MAC" "MDA" "MEX" "MLT" "MNE" "MYS"
## [45] "NLD" "NOR" "NZL" "PER" "POL" "PRT" "QAT" "ROU" "RUS" "SGP" "SVK"
## [56] "SVN" "SWE" "TAP" "THA" "TTO" "TUN" "TUR" "URY" "USA"
levels(escs_2009$cnt) <- c("Albania","United Arab Emirates","Argentina","Australia",
"Austria","Belgium","Bulgaria","Brazil","Canada",
"Switzerland","Chile","Colombia","Costa Rica",
"Czech Republic","Germany","Denmark",
"Spain","Estonia","Finland","France","United Kingdom",
"Georgia","Greece","Hong Kong-China","Croatia","Hungary",
"Indonesia","Ireland","Iceland","Israel", "Italy","Jordan",
"Japan","Kazakhstan","Korea","Lithuania","Luxembourg",
"Latvia","Macao-China","Republic of Moldova","Mexico",
"Malta","Montenegro","Malaysia","Netherlands","Norway",
"New Zealand","Peru","Poland","Portugal","Qatar","Romania",
"Russian Federation","Singapore","Slovak Republic",
"Slovenia","Sweden","Chinese Taipei","Thailand",
"Trinidad and Tobago","Tunisia","Turkey","Uruguay",
"United States")
levels(escs_2009$cnt)
## [1] "Albania" "United Arab Emirates" "Argentina"
## [4] "Australia" "Austria" "Belgium"
## [7] "Bulgaria" "Brazil" "Canada"
## [10] "Switzerland" "Chile" "Colombia"
## [13] "Costa Rica" "Czech Republic" "Germany"
## [16] "Denmark" "Spain" "Estonia"
## [19] "Finland" "France" "United Kingdom"
## [22] "Georgia" "Greece" "Hong Kong-China"
## [25] "Croatia" "Hungary" "Indonesia"
## [28] "Ireland" "Iceland" "Israel"
## [31] "Italy" "Jordan" "Japan"
## [34] "Kazakhstan" "Korea" "Lithuania"
## [37] "Luxembourg" "Latvia" "Macao-China"
## [40] "Republic of Moldova" "Mexico" "Malta"
## [43] "Montenegro" "Malaysia" "Netherlands"
## [46] "Norway" "New Zealand" "Peru"
## [49] "Poland" "Portugal" "Qatar"
## [52] "Romania" "Russian Federation" "Singapore"
## [55] "Slovak Republic" "Slovenia" "Sweden"
## [58] "Chinese Taipei" "Thailand" "Trinidad and Tobago"
## [61] "Tunisia" "Turkey" "Uruguay"
## [64] "United States"
colnames(escs_2009)[1:3] <- c("CNT","SCHOOLID","StIDStd")
pisa_2009_stu <- merge(pisa_2009_stu,escs_2009,by=c("CNT","SCHOOLID","StIDStd") ,all=TRUE)
# 2012
levels(escs_2012$cnt)
## [1] "ALB" "ARE" "ARG" "AUS" "AUT" "BEL" "BGR" "BRA" "CAN" "CHE" "CHL"
## [12] "COL" "CRI" "CZE" "DEU" "DNK" "ESP" "EST" "FIN" "FRA" "GBR" "GRC"
## [23] "HKG" "HRV" "HUN" "IDN" "IRL" "ISL" "ISR" "ITA" "JOR" "JPN" "KAZ"
## [34] "KOR" "LTU" "LUX" "LVA" "MAC" "MEX" "MNE" "MYS" "NLD" "NOR" "NZL"
## [45] "PER" "POL" "PRT" "QAT" "QUC" "ROU" "RUS" "SGP" "SVK" "SVN" "SWE"
## [56] "TAP" "THA" "TUN" "TUR" "URY" "USA" "VNM"
levels(escs_2012$cnt) <- c("Albania","United Arab Emirates","Argentina","Australia",
"Austria","Belgium",
"Bulgaria","Brazil","Canada",
"Switzerland","Chile","Colombia","Costa Rica",
"Czech Republic","Germany","Denmark",
"Spain","Estonia","Finland","France","United Kingdom",
"Greece","Hong Kong-China",
"Croatia","Hungary","Indonesia","Ireland","Iceland",
"Israel","Italy","Jordan","Japan","Kazakhstan","Korea",
"Lithuania","Luxembourg","Latvia","Macao-China",
"Mexico","Montenegro","Malaysia","Netherlands","Norway",
"New Zealand","Peru","Poland","Portugal","Qatar",
"Shanghai-China","Romania","Russian Federation","Singapore",
"Slovak Republic","Slovenia","Sweden","Chinese Taipei",
"Thailand","Tunisia","Turkey",
"Uruguay","United States of America","Viet Nam")
levels(escs_2012$cnt)
## [1] "Albania" "United Arab Emirates"
## [3] "Argentina" "Australia"
## [5] "Austria" "Belgium"
## [7] "Bulgaria" "Brazil"
## [9] "Canada" "Switzerland"
## [11] "Chile" "Colombia"
## [13] "Costa Rica" "Czech Republic"
## [15] "Germany" "Denmark"
## [17] "Spain" "Estonia"
## [19] "Finland" "France"
## [21] "United Kingdom" "Greece"
## [23] "Hong Kong-China" "Croatia"
## [25] "Hungary" "Indonesia"
## [27] "Ireland" "Iceland"
## [29] "Israel" "Italy"
## [31] "Jordan" "Japan"
## [33] "Kazakhstan" "Korea"
## [35] "Lithuania" "Luxembourg"
## [37] "Latvia" "Macao-China"
## [39] "Mexico" "Montenegro"
## [41] "Malaysia" "Netherlands"
## [43] "Norway" "New Zealand"
## [45] "Peru" "Poland"
## [47] "Portugal" "Qatar"
## [49] "Shanghai-China" "Romania"
## [51] "Russian Federation" "Singapore"
## [53] "Slovak Republic" "Slovenia"
## [55] "Sweden" "Chinese Taipei"
## [57] "Thailand" "Tunisia"
## [59] "Turkey" "Uruguay"
## [61] "United States of America" "Viet Nam"
colnames(escs_2012)[1:3] <- c("CNT","SCHOOLID","StIDStd")
pisa_2012_stu <- merge(pisa_2012_stu,escs_2012,by=c("CNT","SCHOOLID","StIDStd") ,all=TRUE)
# Simdide 2003, 2006, 2009, 2012,2015 yillarinda 2015 icin yaptigimiz gibi Turkiye verisini suzelim.
pisa_2015_stu_TUR <- subset(pisa_2015_stu,CNT=='Turkey')
pisa_2012_stu_TUR <- subset(pisa_2012_stu,CNT=="Turkey")
pisa_2009_stu_TUR <- subset(pisa_2009_stu,CNT=='Turkey')
pisa_2006_stu_TUR <- subset(pisa_2006_stu,CNT=='Turkey')
pisa_2003_stu_TUR <- subset(pisa_2003_stu,CNT=='TUR')
# OECD verisini suzelim
pisa_2015_stu_OECD <- subset(pisa_2015_stu,OECD=="Yes")
pisa_2012_stu_OECD <- subset(pisa_2012_stu,OECD=="OECD")
pisa_2009_stu_OECD <- subset(pisa_2009_stu,OECD=="OECD")
pisa_2006_stu_OECD <- subset(pisa_2006_stu,OECD=="OECD")
pisa_2003_stu_OECD <- subset(pisa_2003_stu,OECD=="OECD country")
# AB verisini suzelim
AB <- c("AUT","BEL","BGR","HRV","CYP","CZE","DNK","EST","FIN","FRA","DEU","GRC","HUN",
"IRL","ITA","LVA","LTU","LUX","MLT","NLD","POL","PRT","ROU","SVK","SVN","ESP",
"SWE")
AB2 <- c("Austria","Belgium","Bulgaria","Croatia","Cyprus","Czech Republic","Denmark",
"Estonia","Finland","France","Germany","Greece","Hungary","Ireland","Italy",
"Latvia","Lithuania","Luxembourg","Malta","Netherlands","Poland","Portugal",
"Romania","Slovak Republic","Slovenia ","Spain","Sweden")
AB3 <- c("Austria","Belgium","Bulgaria","Croatia","Cyprus","Czech Republic","Denmark",
"Estonia","Finland","France","Germany","Greece","Hungary","Ireland","Italy",
"Latvia","Lithuania","Luxembourg","Malta","Netherlands","Poland","Portugal",
"Romania","Slovak Republic","Slovenia","Spain","Sweden")
pisa_2003_stu_AB <- subset(pisa_2003_stu, CNT %in% AB)
pisa_2006_stu_AB <- subset(pisa_2006_stu, CNT %in% AB2)
pisa_2009_stu_AB <- subset(pisa_2009_stu, CNT %in% AB3)
pisa_2012_stu_AB <- subset(pisa_2012_stu, CNT %in% AB3)
pisa_2015_stu_AB <- subset(pisa_2015_stu, CNT %in% AB3)
Sinif Seviyesi ve PISA puanlari
Matematik
m2003 <- pisa.mean.pv(pvlabel="MATH",data=pisa_2003_stu_TUR,by="ST01Q01")
colnames(m2003)[1]="SinifSeviyesi"
m2006 <- pisa.mean.pv(pvlabel="MATH",data=pisa_2006_stu_TUR,by="ST01Q01")
colnames(m2006)[1]="SinifSeviyesi"
m2009<- pisa.mean.pv(pvlabel="MATH",data=pisa_2009_stu_TUR,by="ST01Q01")
colnames(m2009)[1]="SinifSeviyesi"
m2012 <- pisa.mean.pv(pvlabel="MATH",data=pisa_2012_stu_TUR,by="ST01Q01")
colnames(m2012)[1]="SinifSeviyesi"
m2015 <- pisa2015.mean.pv(pvlabel="MATH",data=pisa_2015_stu_TUR,by="ST001D01T")
colnames(m2015)[1]="SinifSeviyesi"
m <- rbind(m2006,m2009,m2012,m2015)
m <- m[c(3,4,8,9,14,15,20,21),]
m$year <- c(rep(1,2),rep(2,2),rep(3,2),rep(4,2))
m$Mean2 <- round(m$Mean)
m[7:8,1] <- c(9,10)
m[,1] <- factor(as.character(m[,1]))
ggplot(m, aes(x=year, y=Mean,shape=SinifSeviyesi)) +
theme_bw() +
geom_errorbar(aes(ymin=Mean-1.96*s.e., ymax=Mean+1.96*s.e.),position = position_dodge(0.2),lty=2,colour="gray50",width=.2) +
geom_point(size=4, fill="black",position = position_dodge(0.2)) +
geom_line(position = position_dodge(0.2))+
scale_x_discrete(limit = 1:5,labels=c("2006","2009","2012","2015"))+
scale_y_continuous(limit = c(350,500)) +
labs(title = " MATEMATIK",
x = "YIL", y = "PISA PUANI",
shape="Sinif Duzeyi")+
theme(axis.title= element_text(size = 15),
axis.text= element_text(size = 12),
title = element_text(size = 20),
legend.justification=c(-0.5,-0.2),
legend.position=c(0,0),
legend.text=element_text(size = 12)
) +
annotation_custom(grob = textGrob("@pisa_turkiye"),
xmin = 4.25, xmax = 4.25, ymin =490, ymax = 490)+
geom_text(aes(y=Mean,label=Mean2),stat= "identity", position=position_dodge(.2),vjust = -1.5,hjust=1)
Okuma
m2003 <- pisa.mean.pv(pvlabel="READ",data=pisa_2003_stu_TUR,by="ST01Q01")
colnames(m2003)[1]="SinifSeviyesi"
m2006 <- pisa.mean.pv(pvlabel="READ",data=pisa_2006_stu_TUR,by="ST01Q01")
colnames(m2006)[1]="SinifSeviyesi"
m2009<- pisa.mean.pv(pvlabel="READ",data=pisa_2009_stu_TUR,by="ST01Q01")
colnames(m2009)[1]="SinifSeviyesi"
m2012 <- pisa.mean.pv(pvlabel="READ",data=pisa_2012_stu_TUR,by="ST01Q01")
colnames(m2012)[1]="SinifSeviyesi"
m2015 <- pisa2015.mean.pv(pvlabel="READ",data=pisa_2015_stu_TUR,by="ST001D01T")
colnames(m2015)[1]="SinifSeviyesi"
m <- rbind(m2006,m2009,m2012,m2015)
m <- m[c(3,4,8,9,14,15,20,21),]
m$year <- c(rep(1,2),rep(2,2),rep(3,2),rep(4,2))
m$Mean2 <- round(m$Mean)
m[7:8,1] <- c(9,10)
m[,1] <- factor(as.character(m[,1]))
ggplot(m, aes(x=year, y=Mean,shape=SinifSeviyesi)) +
theme_bw() +
geom_errorbar(aes(ymin=Mean-1.96*s.e., ymax=Mean+1.96*s.e.),position = position_dodge(0.2),lty=2,colour="gray50",width=.2) +
geom_point(size=4, fill="black",position = position_dodge(0.2)) +
geom_line(position = position_dodge(0.2))+
scale_x_discrete(limit = 1:5,labels=c("2006","2009","2012","2015"))+
scale_y_continuous(limit = c(350,525)) +
labs(title = " OKUMA BECERILERI",
x = "YIL", y = "PISA PUANI",
shape="Sinif Duzeyi")+
theme(axis.title= element_text(size = 15),
axis.text= element_text(size = 12),
title = element_text(size = 20),
legend.justification=c(-0.5,-0.2),
legend.position=c(0,0),
legend.text=element_text(size = 12)
) +
annotation_custom(grob = textGrob("@pisa_turkiye"),
xmin = 4.25, xmax = 4.25, ymin =490, ymax = 490)+
geom_text(aes(y=Mean,label=Mean2),stat= "identity", position=position_dodge(.2),vjust = -1.5,hjust=1)
Fen
m2003 <- pisa.mean.pv(pvlabel="SCIE",data=pisa_2003_stu_TUR,by="ST01Q01")
colnames(m2003)[1]="SinifSeviyesi"
m2006 <- pisa.mean.pv(pvlabel="SCIE",data=pisa_2006_stu_TUR,by="ST01Q01")
colnames(m2006)[1]="SinifSeviyesi"
m2009<- pisa.mean.pv(pvlabel="SCIE",data=pisa_2009_stu_TUR,by="ST01Q01")
colnames(m2009)[1]="SinifSeviyesi"
m2012 <- pisa.mean.pv(pvlabel="SCIE",data=pisa_2012_stu_TUR,by="ST01Q01")
colnames(m2012)[1]="SinifSeviyesi"
m2015 <- pisa2015.mean.pv(pvlabel="SCIE",data=pisa_2015_stu_TUR,by="ST001D01T")
colnames(m2015)[1]="SinifSeviyesi"
m <- rbind(m2006,m2009,m2012,m2015)
m <- m[c(3,4,8,9,14,15,20,21),]
m$year <- c(rep(1,2),rep(2,2),rep(3,2),rep(4,2))
m$Mean2 <- round(m$Mean)
m[7:8,1] <- c(9,10)
m[,1] <- factor(as.character(m[,1]))
ggplot(m, aes(x=year, y=Mean,shape=SinifSeviyesi)) +
theme_bw() +
geom_errorbar(aes(ymin=Mean-1.96*s.e., ymax=Mean+1.96*s.e.),position = position_dodge(0.2),lty=2,colour="gray50",width=.2) +
geom_point(size=4, fill="black",position = position_dodge(0.2)) +
geom_line(position = position_dodge(0.2))+
scale_x_discrete(limit = 1:5,labels=c("2006","2009","2012","2015"))+
scale_y_continuous(limit = c(350,525)) +
labs(title = " FEN",
x = "YIL", y = "PISA PUANI",
shape="Sinif Duzeyi")+
theme(axis.title= element_text(size = 15),
axis.text= element_text(size = 12),
title = element_text(size = 20),
legend.justification=c(-0.5,-0.2),
legend.position=c(0,0),
legend.text=element_text(size = 12)
) +
annotation_custom(grob = textGrob("@pisa_turkiye"),
xmin = 4.25, xmax = 4.25, ymin =490, ymax = 490)+
geom_text(aes(y=Mean,label=Mean2),stat= "identity", position=position_dodge(.2),vjust = -2.,hjust=1.5)
Cografi Bolge ve PISA puanlari
# Bolgelerin belirlenmesi
# 2015
pisa_2015_stu_TUR$bolge <- NA
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 01: TR1 BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 02: TR1 GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 03: TR1 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "ISTANBUL"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 04: TR2 BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 05: TR2 GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 06: TR2 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "BatiMarmara"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 07: TR3 BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 08: TR3 GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 09: TR3 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "Ege"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 10: TR4 BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 11: TR4 GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 12: TR4 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "DoguMarmara"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 13: TR5 BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 14: TR5 GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 15: TR5 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "BatiAnadolu"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 16: TR6 BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 17: TR6 GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 18: TR6 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "Akdeniz"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 19: TR7 BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 20: TR7 GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 21: TR7 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "OrtaAnadolu"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 22: TR8 BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 23: TR8 GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 24: TR8 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "BatiKaradeniz"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 25: TR9 BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 26: TR9 GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 27: TR9 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "DoguKaradeniz"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 28: TRA BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 29: TRA GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 30: TRA VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "KuzeydoguAnadolu"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 31: TRB BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 32: TRB GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 33: TRB VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "OrtadoguAnadolu"
pisa_2015_stu_TUR[pisa_2015_stu_TUR$STRATUM=="TUR - stratum 34: TRC BASIC EDUCATION" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 35: TRC GENERAL SECONDARY" |
pisa_2015_stu_TUR$STRATUM=="TUR - stratum 36: TRC VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "GuneydoguAnadolu"
# 2012
pisa_2012_stu_TUR$bolge <- NA
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 01 : TR1 PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 02 : TR1 GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 03 : TR1 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "ISTANBUL"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 04 : TR2 PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 05 : TR2 GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 06 : TR2 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "BatiMarmara"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 07 : TR3 PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 08 : TR3 GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 09 : TR3 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "Ege"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 10 : TR4 PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 11 : TR4 GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 12 : TR4 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "DoguMarmara"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 14 : TR5 PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 15 : TR5 GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 16 : TR5 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "BatiAnadolu"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 18 : TR6 PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 19 : TR6 GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 20 : TR6 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "Akdeniz"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 21 : TR7 PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 22 : TR7 GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 23 : TR7 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "OrtaAnadolu"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 24 : TR8 PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 25 : TR8 GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 26 : TR8 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "BatiKaradeniz"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 27 : TR9 PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 28 : TR9 GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 29 : TR9 VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "DoguKaradeniz"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 30 : TRA PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 31 : TRA GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 32 : TRA VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "KuzeydoguAnadolu"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 33 : TRB PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 34 : TRB GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 35 : TRB VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "OrtadoguAnadolu"
pisa_2012_stu_TUR[pisa_2012_stu_TUR$STRATUM=="TUR - stratum 36 : TRC PRIMARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 37 : TRC GENERAL SECONDARY" |
pisa_2012_stu_TUR$STRATUM=="TUR - stratum 38 : TRC VOCATIONAL AND TECHNICAL SECONDARY",]$bolge <- "GuneydoguAnadolu"
# Matematik
p2012 <- pisa.mean.pv(pvlabel="MATH",data=pisa_2012_stu_TUR,by="bolge")[1:12,]
p2015 <- pisa2015.mean.pv(pvlabel="MATH",data=pisa_2015_stu_TUR,by="bolge")
p <- rbind(p2012,p2015)
p <- p[order(p$bolge),]
p$Mean2 <- round(p$Mean)
p$year <- factor(c(2012,2015))
p$bolge <- factor(p$bolge,
levels = c("BatiMarmara","DoguMarmara","OrtaAnadolu","Ege","BatiAnadolu","ISTANBUL","Akdeniz",
"DoguKaradeniz","KuzeydoguAnadolu","BatiKaradeniz","GuneydoguAnadolu","OrtadoguAnadolu"))
ggplot(p, aes(x=bolge, y=Mean,fill=year)) +
geom_bar(stat='identity',position=position_dodge(),width=.75) +
scale_y_continuous(limit = c(0,500))+
theme_bw()+
geom_text(aes(y=Mean,label=Mean2),
stat= "identity", position=position_dodge(1),vjust = -.5)+
labs(title =" MATEMATIK",
x = "Bolge", y = "PISA PUANI",
fill=" ")+
theme(axis.title= element_text(size = 15),
axis.text= element_text(size = 12),
axis.text.x = element_text(angle = 90, hjust = .5,size=10),
title = element_text(size = 18),
legend.text=element_text(size = 12)) +
annotation_custom(grob = textGrob("@pisa_turkiye"),
xmin = 11.5, xmax = 11.5, ymin = 500, ymax = 500)
# OKUMA
p2012 <- pisa.mean.pv(pvlabel="READ",data=pisa_2012_stu_TUR,by="bolge")[1:12,]
p2015 <- pisa2015.mean.pv(pvlabel="READ",data=pisa_2015_stu_TUR,by="bolge")
p <- rbind(p2012,p2015)
p <- p[order(p$bolge),]
p$Mean2 <- round(p$Mean)
p$year <- factor(c(2012,2015))
p$bolge <- factor(p$bolge,
levels = c("BatiMarmara","DoguMarmara","OrtaAnadolu","Ege","BatiAnadolu","ISTANBUL","Akdeniz",
"DoguKaradeniz","KuzeydoguAnadolu","BatiKaradeniz","GuneydoguAnadolu","OrtadoguAnadolu"))
ggplot(p, aes(x=bolge, y=Mean,fill=year)) +
geom_bar(stat='identity',position=position_dodge(),width=.75) +
scale_y_continuous(limit = c(0,550))+
theme_bw()+
geom_text(aes(y=Mean,label=Mean2),
stat= "identity", position=position_dodge(1),vjust = -.5)+
labs(title =" OKUMA BECERILERI",
x = "Bolge", y = "PISA PUANI",
fill=" ")+
theme(axis.title= element_text(size = 15),
axis.text= element_text(size = 12),
axis.text.x = element_text(angle = 90, hjust = .5,size=10),
title = element_text(size = 18),
legend.text=element_text(size = 12)) +
annotation_custom(grob = textGrob("@pisa_turkiye"),
xmin = 11.5, xmax = 11.5, ymin = 500, ymax = 500)
# FEN
p2012 <- pisa.mean.pv(pvlabel="SCIE",data=pisa_2012_stu_TUR,by="bolge")[1:12,]
p2015 <- pisa2015.mean.pv(pvlabel="SCIE",data=pisa_2015_stu_TUR,by="bolge")
p <- rbind(p2012,p2015)
p <- p[order(p$bolge),]
p$Mean2 <- round(p$Mean)
p$year <- factor(c(2012,2015))
p$bolge <- factor(p$bolge,
levels = c("BatiMarmara","DoguMarmara","OrtaAnadolu","Ege","BatiAnadolu","ISTANBUL","Akdeniz",
"DoguKaradeniz","KuzeydoguAnadolu","BatiKaradeniz","GuneydoguAnadolu","OrtadoguAnadolu"))
ggplot(p, aes(x=bolge, y=Mean,fill=year)) +
geom_bar(stat='identity',position=position_dodge(),width=.75) +
scale_y_continuous(limit = c(0,525))+
theme_bw()+
geom_text(aes(y=Mean,label=Mean2),
stat= "identity", position=position_dodge(1),vjust = -.5)+
labs(title =" FEN",
x = "Bolge", y = "PISA PUANI",
fill=" ")+
theme(axis.title= element_text(size = 15),
axis.text= element_text(size = 12),
axis.text.x = element_text(angle = 90, hjust = .5,size=10),
title = element_text(size = 18),
legend.text=element_text(size = 12)) +
annotation_custom(grob = textGrob("@pisa_turkiye"),
xmin = 11.5, xmax = 11.5, ymin = 520, ymax = 520)
