library(WDI)
SE.PRM.UNER.MA “okula gitmeyen çocuklar,ılkokul,erkek SE.XPD.TOTL.GB.ZS”Eğitime yönelik kamu harcamaları, toplam (kamu harcamalarının yüzdesi)”
data <- WDI(indicator= c("SE.PRM.UNER.MA","SE.XPD.TOTL.GB.ZS"))
2002
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.1 ✔ tibble 3.2.1
## ✔ lubridate 1.9.3 ✔ tidyr 1.3.1
## ✔ purrr 1.0.2
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
data2002 <- data %>% filter(year==2002)
dataID <- data %>% filter(country=="Indonesia")
library(ggplot2)
ggplot(dataID,aes(year,SE.PRM.UNER.MA)) +geom_line()
## Warning: Removed 16 rows containing missing values or values outside the scale range
## (`geom_line()`).
ggplot(dataID,aes(year,SE.XPD.TOTL.GB.ZS)) +geom_line()
## Warning: Removed 49 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Rgresyon
model <- lm(SE.PRM.UNER.MA ~ SE.XPD.TOTL.GB.ZS, data = dataID)
summary(model)
##
## Call:
## lm(formula = SE.PRM.UNER.MA ~ SE.XPD.TOTL.GB.ZS, data = dataID)
##
## Residuals:
## 49 54 55 57 58 59
## -71033 -167707 -107039 -99120 108144 336755
## attr(,"label")
## [1] "Children out of school, primary, male"
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -134308 515111 -0.261 0.807
## SE.XPD.TOTL.GB.ZS 28178 31027 0.908 0.415
##
## Residual standard error: 211900 on 4 degrees of freedom
## (58 observations effacées parce que manquantes)
## Multiple R-squared: 0.1709, Adjusted R-squared: -0.03632
## F-statistic: 0.8247 on 1 and 4 DF, p-value: 0.4152