---
title: "Precept 6 Problem Set"
output:
html_document:
df_print: paged
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
### Problem 1
Suppose 65% SML201 students like World Coffee better than Hoagie Haven. We selected a random sample of 20 SML201 students, and asked them which they prefer. What is the probability that more than 18 students said "World Coffee"? Write R code to compute the actual probability.
Hint:
* We solved a very similar problem in class on April 2 with coin tosses. Each student answer can be thought of as being like a coin toss. Decide whether you want "Heads" to represent HH or WC, and then solve the problem using `pbinom`, just like we did in class.
#### Solution
This is like asking about the probability of a coin's coming up heads 18 times or more out of 20 when the probability of the coin's coming up heads is 65%:
```{r}
1 - pbinom(q = 18, size = 20, prob = 0.65)
```
The answer is 0.2%.
Here's another way to compute the answer:
```{r}
sum(dbinom(x = c(19, 20), size = 20, prob = 0.65))
```
### Problem 2
In class, we saw several ways to compute the cumulative probability for the binomial distribution: we used `pbinom`; we summed up the outputs of `dbinom`; we also generated a large sample using `rbinom`, and then computed the proportion of the generated numbers that was under a certain threshold.
#### Part 2(a)
Write a function named `MyPbinom1`, which works just like `pbinom`. You may use `dbinom` but not `rbinom` in the function you write.
```{r}
MyPbinom1 <- function(q, size, prob){
return(sum(dbinom(x = 0:q, size = size, prob = prob )))
}
MyPbinom1(q = 2, size = 10, prob = 0.45)
pbinom(q = 2, size = 10, prob = 0.45)
```
#### Part 2(b)
Write a function named `MyPbinom2`, which works just like `pbinom`. You may use `rbinom` but not `dbinom` in the function you write.
```{r}
MyPbinom2 <- function(q, size, prob){
sample <- rbinom(n = 10000000, size = size, prob = prob)
return(mean(sample <= q))
}
MyPbinom2(q = 2, size = 10, prob = 0.45)
pbinom(q = 2, size = 10, prob = 0.45)
```