SE.XPD.PRIM.PC.ZS ( öğrenci başına düşen devlet harcamaları ) SE.XPD.TOTL.GD.ZS ( eğitime yönelik devlet harcamaları )
##dünya bankasından veri indirmek
library(WDI)
data <- WDI(indicator = c("SE.XPD.PRIM.PC.ZS", "SE.XPD.TOTL.GD.ZS" ))
##kesit veri
library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ 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
data2003 <- data %>% filter(year == 2003)
##zaman serisi
dataTR <- data %>% filter (country == "TURKIYE")
library(ggplot2)
ggplot(dataTR, aes("year","SE.XPD.PRIM.PC.ZS")) + geom_line()
## `geom_line()`: Each group consists of only one observation.
## ℹ Do you need to adjust the group aesthetic?
ggplot(dataTR, aes(SE.XPD.TOTL.GD.ZS)) + geom_histogram()
ggplot(dataTR, aes(SE.XPD.PRIM.PC.ZS, SE.XPD.TOTL.GD.ZS)) + geom_point()
##regresyon
model <-lm (SE.XPD.PRIM.PC.ZS ~ SE.XPD.TOTL.GD.ZS , data = data)
summary(model)
##
## Call:
## lm(formula = SE.XPD.PRIM.PC.ZS ~ SE.XPD.TOTL.GD.ZS, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -25.166 -2.896 -0.771 2.304 46.721
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3.33935 0.35878 9.308 <2e-16 ***
## SE.XPD.TOTL.GD.ZS 2.75671 0.07501 36.752 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 5.149 on 1795 degrees of freedom
## (15227 observations deleted due to missingness)
## Multiple R-squared: 0.4294, Adjusted R-squared: 0.4291
## F-statistic: 1351 on 1 and 1795 DF, p-value: < 2.2e-16