Analisis Data CAD Alizadeh

#memuat library yang dibutuhkan
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 1.9.4     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(gridExtra)

## 
## Attaching package: 'gridExtra'
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## The following object is masked from 'package:dplyr':
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##     combine

library(readxl)
knitr::opts_chunk$set(echo = TRUE)

# Membaca dan menampilkan data
CAD_alizadeh <- read_excel("CAD alizadeh.xls")
View(CAD_alizadeh)

# 1. Age vs Length
plot1 <- ggplot(CAD_alizadeh, aes(x=Age, y=Length)) +
geom_point(color="#FF6B6B", size=2) +
geom_smooth(method=lm, color="#4ECDC4") +
labs(title="Age vs Length", x="Age", y="Length") +
theme_minimal()

# 2. Age vs Weight
plot2 <- ggplot(CAD_alizadeh, aes(x=Age, y=Weight)) +
geom_point(color="#45B7D1", size=2) +
geom_smooth(method=lm, color="#96CEB4") +
labs(title="Age vs Weight", x="Age", y="Weight") +
theme_minimal()

# 3. Age vs PR
plot3 <- ggplot(CAD_alizadeh, aes(x=Age, y=PR)) +
geom_point(color="#D65076", size=2) +
geom_smooth(method=lm, color="#EEB868") +
labs(title="Age vs PR", x="Age", y="PR") +
theme_minimal()

#menampilkan scatterplot
grid.arrange(plot1, plot2, plot3, ncol=2)

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

#hitung korelasi
cor_age_length <- cor(CAD_alizadeh$Age, CAD_alizadeh$Length)
cor_age_weight <- cor(CAD_alizadeh$Age, CAD_alizadeh$Weight)
cor_age_pr <- cor(CAD_alizadeh$Age, CAD_alizadeh$PR)

#mencetak korelasi
cat("Correlations:\n", "age-length:", round(cor_age_length, 3), "\n", "age-weight:", round(cor_age_weight, 3), "\n", "age-pr:", round(cor_age_pr, 3))

## Correlations:
##  age-length: -0.164 
##  age-weight: -0.265 
##  age-pr: 0.024