FFFiend

set.seed(71)

num_friends = 20

edward_measurements <- rnorm(num_friends, mean = 180, sd = 5)
hugo_measurements <- rnorm(num_friends, mean = 180, sd = 11)
lucy_measurements <- rnorm(num_friends, mean = 180, sd = 7)


height_data <- data.frame(

FFFiend

# Set seed for reproducibility
set.seed(123)

# Generate random data for independent variables
n <- 100  # Number of observations
earth <- rnorm(n)
fire <- rnorm(n)
wind <- rnorm(n)
water <- rnorm(n)

FFFiend

# Set seed for reproducibility
set.seed(123)

# Number of observations
n <- 1000

# Simulate age group (categorical with 4 levels)
age_group <- sample(1:4, n, replace = TRUE)

# Simulate gender (binary: 0 = male, 1 = female)

FFFiend

# Set seed for reproducibility
set.seed(123)

# Number of observations
n <- 1000

# Simulate age group (categorical with 4 levels)
age_group <- sample(1:4, n, replace = TRUE)

# Simulate gender (binary: 0 = male, 1 = female)

FFFiend

"""
Union Find template for me.
"""
MAX_SIZE = 10000005

class UnionFind:
  
    def __init__(self):
        self.height = [0]*MAX_SIZE
        self.father=[0]*MAX_SIZE

FFFiend

# Load required libraries
library(ggplot2)
library(rstanarm)

# Generate sample data
set.seed(123)
data <- data.frame(
  age_group = sample(c("18-30", "31-45", "46-60", "61+"), 100, replace = TRUE),
  gender = sample(c("Male", "Female"), 100, replace = TRUE),
  income_group = sample(c("Low", "Medium", "High"), 100, replace = TRUE),

FFFiend

# Load required libraries
library(dplyr)
library(ggplot2)

# Set seed for reproducibility
set.seed(123)

# Define hospitals
hospitals <- c("Hospital A", "Hospital B", "Hospital C", "Hospital D", "Hospital E")