session3.R_essentials_for_advanced_R_programming.Rmd

---
title: "session3.R_essentials_for_advanced_R_programming"
author: "Sima"
date: "2024-08-27"
output: html_document
---

warm-up question:

```{r setup, include=FALSE}
install.packages("beepr")
library(beepr)
beepr::beep()
k=1-11
beepr::beep(k)
?beep
```



```{r cars}
for (k in 1:11) {
  beepr::beep(k)
  Sys.sleep(2)  # Pause for 2 seconds
}
```



```{r pressure, echo=FALSE}
# Loop to play each sound with a random pause between each beep
for (k in 1:11) {
  beepr::beep(k)
  Sys.sleep(runif(1, min = 1, max = 5))  
}

```

```{r}
cumulative_sum_with_beep <- function(vec, sound = 1) {
  n <- length(vec)
  cumsum_vec <- numeric(n)
  
  # Loop to calculate the cumulative sum
  for (i in 1:n) {
    if (i == 1) {
      cumsum_vec[i] <- vec[i]
    } else {
      cumsum_vec[i] <- cumsum_vec[i - 1] + vec[i]
    }
  }
  
  # Play the beep sound
  beepr::beep(sound)
  
  # Create and return a matrix with original vector and cumulative sum
  result <- cbind(vec, cumsum_vec)
  return(result)
}

# Example usage
numeric_vector <- c(1, 2, 3, 4, 5)
result_matrix <- cumulative_sum_with_beep(numeric_vector, sound = 2)

# Check result
print(result_matrix)

```



```{r}
data("HairEyeColor")
HairEyeColor
attributes(HairEyeColor)
```


```{r}
y <- 1:11
x <- 1:11
f <- lm(y~x)
mode(f)

x <- list(1,2,3)
x
x[[1]]
x[1]
x[[1]] |> str()
x[1] |> str()
```


```{r}
x<- matrix(1:10, nrow=2)
x
```
```{r}
x[1,c(2,5)]
```
```{r}
rownames(x) <- 2010:2011
colnames(x) <- c("SLC", "LA","Milcreek","Tennesse","San")
x[,c("SLC","San")]
dim(x["2010",c("SLC","San")])
##because it doesnt show 2010 so it doesnt have dimension
x["2010",c("SLC","San")]
dim(x[,c("SLC","San")])
```


```{r}
x=1:11
y=1:11
f=lm(y~x)
summary(f)
summary.lm(f)
predict(f)
predict.lm(f)
```
```{r}
# Name as a vector of individual letters
name_vector <- c("S", "I", "M", "A")
LETTERS
positions=1:26
names(positions)=LETTERS

positions[c("S","I","M","A")]

alphabet_numbers <- match(name_vector, LETTERS)

# Assign names to the vector
names(alphabet_numbers) <- name_vector

# Print the result
alphabet_numbers


name_vector <- c("J", "O", "H", "N")

# Find the position of each letter in the alphabet
alphabet_numbers <- match(name_vector, LETTERS)

# Assign names to the vector
names(alphabet_numbers) <- name_vector
alphabet_numbers


```
```{r}
rep(0:1,times=5)
names(tx)=1:10
tx[tx==1]

which(tx==1)
```

```{r}
x="yes"
if(x=="yes"){
  print("I will take the project")
}else{
    print("I wont take it")
  }

```


```{r}
urn_1=rep(c("blue","yellow"),c(10,8))
urn_2=rep(c("blue","yellow"),c(6,6))
prob_blue_urn1 <- sum(urn_1 == "blue") / length(urn_1)

prob_yellow_urn1 <- sum(urn_1 == "yellow") / length(urn_1)

prob_blue_if_blue_added <- (sum(urn_2 == "blue") + 1) / (length(urn_2) + 1)

prob_blue_if_yellow_added <- sum(urn_2 == "blue") / (length(urn_2) + 1)

# Total probability of drawing a blue ball from urn 2 after one ball is added
prob_blue_urn2 <- (prob_blue_urn1 * prob_blue_if_blue_added) + 
                  (prob_yellow_urn1 * prob_blue_if_yellow_added)

prob_blue_urn2



estimate_blue_probability <- function(n_replicates = 100000) {
  blue_draws <- 0
  
  for (i in 1:n_replicates) {
    urn_1 <- rep(c("blue", "yellow"), c(10, 8))
    drawn_marble <- sample(urn_1, 1)
    
    urn_2 <- c(rep(c("blue", "yellow"), c(6, 6)), drawn_marble)
    
    second_draw <- sample(urn_2, 1)
    
    # Check if the second marble is blue
    if (second_draw == "blue") {
      blue_draws <- blue_draws + 1
    }
  }
  
  # Estimate the probability
  estimated_probability <- blue_draws / n_replicates
  
  return(estimated_probability)
}

estimated_prob <- estimate_blue_probability()
estimated_prob


```