# let's create vector with mean 3 and standard deviation 1
# normally distributed in interval 0-5
# 100 observations

set.seed(123)
x <- rnorm(100, mean = 3, sd = 1)
hist(x, breaks = 20, col = "lightblue", main = "Histogram of x", xlab = "x")

# now let's make for loop to create 24*100 observations
# and store them in 24 vectors a - x
# each vector will have different mean, starting from 0.5 and going up by 0.1

for (i in 1:24) {
  assign(paste0("a", letters[i]), rnorm(100, mean = 0.5 + 0.2*i, sd = 1))
}

hist(aw, breaks = 20, col = "lightblue", main = "Histogram of aw", xlab = "aw")

# now let's put all the vectors into one data frame
# variable condition will be the name of the vector
# and variable value will be the value of the vector

df <- data.frame()
for (i in 1:24) {
  df <- rbind(df, data.frame(condition = paste0("a", letters[i]), value = get(paste0("a", letters[i]))))
}

# let's add x as a condition to the data frame

df <- rbind(df, data.frame(condition = "x", value = x))

# now let's make a boxplot

boxplot(value ~ condition, data = df, col = "lightblue", main = "Boxplot of x and aw", xlab = "condition", ylab = "value")

# let's make histogram of two conditions: aa and x from df

# first tidyverse to subset df to only x and aa

library(tidyverse)

df2 <- df %>%
  filter(condition %in% c("x", "aa"))

library(ggplot2)

ggplot(df2, aes(x = value, fill = condition)) +
  geom_histogram(bins = 20, alpha = 0.5, position = "identity") +
  labs(title = "Histogram of x and aa", x = "value", y = "count") +
  theme_minimal()

# let's compute t.test for x and aa

t.test(x, aa, alternative = "two.sided")

# let's load csv of student's names, semicolon separated

students <- read.csv("seznam_export.csv", sep = ";")

# add column condition to students data frame
# and fill it from ab to az
# but in reverse order

students$condition <- paste0("a", letters[26:6])

# students$condition <- sample(c("x", "aa"), nrow(students), replace = TRUE)
# students$condition <- paste0("a", letters[1:nrow(students)])

print(students)

write.csv(students, "students.csv", row.names = FALSE)