26.12.25 dersi

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(ggplot2)
library(palmerpenguins)

## 
## Attaching package: 'palmerpenguins'

## The following objects are masked from 'package:datasets':
## 
##     penguins, penguins_raw

library(broom)

data(penguins)
names(penguins)

## [1] "species"           "island"            "bill_length_mm"   
## [4] "bill_depth_mm"     "flipper_length_mm" "body_mass_g"      
## [7] "sex"               "year"

glimpse(penguins)

## Rows: 344
## Columns: 8
## $ species           <fct> Adelie, Adelie, Adelie, Adelie, Adelie, Adelie, Adel…
## $ island            <fct> Torgersen, Torgersen, Torgersen, Torgersen, Torgerse…
## $ bill_length_mm    <dbl> 39.1, 39.5, 40.3, NA, 36.7, 39.3, 38.9, 39.2, 34.1, …
## $ bill_depth_mm     <dbl> 18.7, 17.4, 18.0, NA, 19.3, 20.6, 17.8, 19.6, 18.1, …
## $ flipper_length_mm <int> 181, 186, 195, NA, 193, 190, 181, 195, 193, 190, 186…
## $ body_mass_g       <int> 3750, 3800, 3250, NA, 3450, 3650, 3625, 4675, 3475, …
## $ sex               <fct> male, female, female, NA, female, male, female, male…
## $ year              <int> 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007, 2007…

penguins_tr <- penguins %>% 
  rename(
    tür=species,
    ada=island,
    gaga_uzunluk=bill_length_mm,
    gaga_derinlik=bill_depth_mm,
    yuzgec_uzunluk=flipper_length_mm,
    kilo=body_mass_g,
    cinsiyet=sex,
    yil=year
  )

penguins_tr <- penguins_tr|>
  select(kilo, yuzgec_uzunluk)
na.omit

## function (object, ...) 
## UseMethod("na.omit")
## <bytecode: 0x13e6ab508>
## <environment: namespace:stats>

ggplot(penguins_tr, aes(x = yuzgec_uzunluk, y= kilo))+
  geom_point() +
  labs(x = "yüzgeç uzunluğu (mm)",
       y = "vücut ağırlığı(gram)",
       title = "yüzgeç uzunluğu ile vücut ağırlığı ilişkisi" )

## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_point()`).

peng_mod<-lm(kilo ~ yuzgec_uzunluk, data = penguins_tr) 
summary(peng_mod)

## 
## Call:
## lm(formula = kilo ~ yuzgec_uzunluk, data = penguins_tr)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -1058.80  -259.27   -26.88   247.33  1288.69 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    -5780.831    305.815  -18.90   <2e-16 ***
## yuzgec_uzunluk    49.686      1.518   32.72   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 394.3 on 340 degrees of freedom
##   (2 observations deleted due to missingness)
## Multiple R-squared:  0.759,  Adjusted R-squared:  0.7583 
## F-statistic:  1071 on 1 and 340 DF,  p-value: < 2.2e-16

coef(peng_mod)

##    (Intercept) yuzgec_uzunluk 
##    -5780.83136       49.68557

ggplot(penguins_tr, aes(x = yuzgec_uzunluk, y = kilo )) + 
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, color = "red") +
  labs(x = "yüzgeç uzunluğu (mm)",
       y = "vücut ağırlığı (gram)",
       title = "basit doğrusal regresyon çizgisi")

## `geom_smooth()` using formula = 'y ~ x'

## Warning: Removed 2 rows containing non-finite outside the scale range
## (`stat_smooth()`).

## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_point()`).

new_peng <- data.frame(yuzgec_uzunluk = 200)
predict(peng_mod, newdata = new_peng)

##        1 
## 4156.282