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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

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,
    yüzgec_uzunluk=flipper_length_mm,
    kilo=body_mass_g,
    cinsiyet=sex,
    yil=year
    
  )

names(penguins_tr)

## [1] "tür"            "ada"            "gaga_uzunluk"   "gaga_derinlik" 
## [5] "yüzgec_uzunluk" "kilo"           "cinsiyet"       "yil"

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

ggplot(penguins_tr,aes(x=yüzgec_uzunluk,y=kilo))+
  geom_point()+
  labs(x="Yüzgeç Uzunluğu (mm)",
       y="Vücut Ağırlığı(gram)",
       title = "Yüzgeç Uzunluğu ile Vücut Ağırlığı İlişkisi")

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

## 
## Call:
## lm(formula = kilo ~ yüzgec_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 ***
## yüzgec_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
## 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) yüzgec_uzunluk 
##    -5780.83136       49.68557

ggplot(penguins_tr,aes(x=yüzgec_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"
       )+
  theme_get()

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

library(MASS)

## 
## Attaching package: 'MASS'

## The following object is masked from 'package:dplyr':
## 
##     select

library(dplyr)
library(ggplot2)

data("survey")

names(survey)

##  [1] "Sex"    "Wr.Hnd" "NW.Hnd" "W.Hnd"  "Fold"   "Pulse"  "Clap"   "Exer"  
##  [9] "Smoke"  "Height" "M.I"    "Age"

ggplot(
  data = survey,
  aes(x=Age,y=Pulse)
  
)+
  geom_point()

## Warning: Removed 45 rows containing missing values or values outside the scale range
## (`geom_point()`).

ggplot(
   data=survey,
   aes(x=Age,y=Pulse)
   
 )+
   geom_point()+
   labs(
    x="Yaş",
    y="Nabız",
    title="Yaş ile Nabız Arasındaki İlişki"
)

## Warning: Removed 45 rows containing missing values or values outside the scale range
## (`geom_point()`).

ggplot(
   data=survey,
   aes(x=Age,y=Pulse)
   
 )+
   geom_point()+
   labs(
    x="Yaş",
    y="Nabız",
    title="Yaş ile Nabız Arasındaki İlişki"
   )+
  geom_smooth(
    se=FALSE,
    color="orange"
  )

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

## Warning: Removed 45 rows containing non-finite outside the scale range
## (`stat_smooth()`).

## Warning: Removed 45 rows containing missing values or values outside the scale range
## (`geom_point()`).

cor(
  survey$Wr.Hnd,
  survey$NW.Hnd,
  use = "pairwise.complete.obs"
  
)

## [1] 0.9483103

  cor(
  survey$Age,
  survey$Pulse,
  use ="pairwise.complete.obs"
)

## [1] -0.1180616

ggplot(
  survey,
  aes(x=Wr.Hnd,y=NW.Hnd)
)+
  geom_point()+
  geom_smooth(
    se=FALSE,
    color="red"
    
  )+
  labs(
    x="Sağ El Genişliği(cm)",
    y="Yazı Yazılmayan El Genişliği(cm)",
    title = "İki El Genişliği Arasındaki İlişki"
    
  )

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

## Warning: Removed 1 row containing non-finite outside the scale range
## (`stat_smooth()`).

## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_point()`).