23.03.2026_5.ders

Bu haftaki konumuz “Lojistik Regresyon”

Bu derse ilişkin yapılacak görevler bu hafta içerisinde yetiştirilememiştir. En kısa zamanda Rpubs’ı güncelleyerek ekleyeceğim hocam. Şimdiden anlayışınız için teşekkür ederim.

library(readr)
heart_transplant <- read_csv("heart_transplant.csv")
## Rows: 103 Columns: 8
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (3): survived, prior, transplant
## dbl (5): id, acceptyear, age, survtime, wait
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
View(heart_transplant)
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.5.3
ggplot(data = heart_transplant, aes(x = age, y = survived)) + 
  geom_jitter(width = 0, height = 0.05, alpha = 0.5)

glm(formula = survived=="alive" ~ age, family = binomial, data = heart_transplant)
## 
## Call:  glm(formula = survived == "alive" ~ age, family = binomial, data = heart_transplant)
## 
## Coefficients:
## (Intercept)          age  
##     1.56438     -0.05847  
## 
## Degrees of Freedom: 102 Total (i.e. Null);  101 Residual
## Null Deviance:       120.5 
## Residual Deviance: 113.7     AIC: 117.7
cheney <- data.frame(age=71, transplant="treatment")
cheney
##   age transplant
## 1  71  treatment

library(“broom”) augment(mod, newdata=cheney, type.predict=“response”)

library(pscl) pR2(mod)