A rate function is \(r(x) = \cos(2x + 7)\). What is \(r'(x)\)?
# install.packages("Deriv")
library(Deriv)
r <- function(x) {
cos(2 * x + 7)
}
r_prime <- Deriv(r)
r_prime
## function (x)
## -(2 * sin(2 * x + 7))
There are nineteen sweets in a jar - 4 blue, 4 red, 4 green, 5 yellow, and 2 lilac. You shake the jar and choose one sweet from the jar without looking and note its color. You shake the jar again, and then choose a second sweet without looking. Answer the following questions.
A. What is the probability both sweets chosen are yellow?
jar1 <- c(rep("Blue",4),rep("Red",4),rep("Green",4),rep("Yellow",5),rep("Lilac",2))
N1 <- 1e5
counter1 <- 0
for (i in 1:N1) {
pick1 <- sample(x = jar1,size = 2,replace = T)
if (all(pick1 == "Yellow")) {
counter1 <- counter1 + 1
}
}
probability1 <- counter1 / N1
cat("The probability both sweets chosen are yellow is:",probability1,"\n")
## The probability both sweets chosen are yellow is: 0.06945
B. What is the probability both sweets chosen are not yellow?
jar2 <- c(rep("Blue",4),rep("Red",4),rep("Green",4),rep("Yellow",5),rep("Lilac",2))
N2 <- 1e5
counter2 <- 0
for (j in 1:N2) {
pick2 <- sample(x = jar2,size = 2,replace = T)
if (all(pick2 != "Yellow")) {
counter2 <- counter2 + 1
}
}
probability2 <- counter2 / N2
cat("The probability both sweets chosen are not yellow is:",probability2,"\n")
## The probability both sweets chosen are not yellow is: 0.54025
Quentin went to a local take-out. How much did he pay for one fries and one nugget?
q3_data <- data.frame(Item = c("Burger","Hot Dog","Fries","Soda","Drumstick","Onion Ring","Coffee","Nugget"),
Price = c(0.89,0.72,0.65,0.58,0.95,0.24,0.99,0.20))
q3_data
## Item Price
## 1 Burger 0.89
## 2 Hot Dog 0.72
## 3 Fries 0.65
## 4 Soda 0.58
## 5 Drumstick 0.95
## 6 Onion Ring 0.24
## 7 Coffee 0.99
## 8 Nugget 0.20
# install.packages("tidyverse")
library(tidyverse)
## Warning: package 'lubridate' was built under R version 4.5.2
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.1 ✔ stringr 1.5.2
## ✔ ggplot2 4.0.0 ✔ tibble 3.3.0
## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.1.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
solution <- q3_data %>%
filter(Item %in% c("Fries","Nugget")) %>%
summarise(Total = sum(Price)) %>%
pull(Total)
cat("Quentin paid $",solution,"for one fries and one nugget.","\n")
## Quentin paid $ 0.85 for one fries and one nugget.