Problem Set # 1

Frank Annie

September 9, 2015

Due Date: September 10, 2015 Total Points: 44

1 Assign to an object x the sum of 3 and 5. Find the square root of the sum (2).

x <- 3+5
sqrt(x)

## [1] 2.828427

Table the following numbers in a vector h: 2 4 0 3 1 0 0 1 2 0 (2).

h = c (2,4,0,3,1,0,0,1,2,0)
table (h)

## h
## 0 1 2 3 4 
## 4 2 2 1 1

2 The following values are the annual number hurricanes that have hit the United States since 1990. Follow the instructions and answer questions by typing the appropriate R commands.

0 1 1 1 0 2 2 1 3 3 0 0 1 2 6 6 0 1 3 0 1

1. Enter the data into R. (2)

hurricances <- c(0,1,1,1,0,2,2,1,3,3,0,0,1,2,6,6,0,1,3,0,1)

2. How many years are there? (2)

length(hurricances)

## [1] 21

3. What is the total number of hurricanes over all years? (2)

sum(hurricances)

## [1] 34

3 Answer the following questions by typing the appropriate R commands.

1. Create a vector of numbers starting with 0 and ending with 25. (2)

num <-0:25

2. What is the length of this vector? (2)

length(num)

## [1] 26

3. Create a new vector from the original vector by subtracting the mean value over all numbers in the vector. (2)

num_mean <-mean(num) 

new_num <-num - num_mean 

4 Suppose you keep track of your mileage each time you fill up. At your last 8 fill-ups the mileage was

65311 65624 65908 66219 66499 66821 67145 67447

1. Enter these numbers into a vector called miles. (2)

miles <-c(65311,65624,65908,66219,66499,66821,67145,67447)

2. Use the function diff() to determine the number of miles between fill-ups. (2)

diff(miles)

## [1] 313 284 311 280 322 324 302

3. What is the maximum, minimum, and mean number of miles between fill-ups? (3)

max(diff(miles))

## [1] 324

min(diff(miles))

## [1] 280

mean(diff(miles))

## [1] 305.1429

5 Create the following sequences using the seq() and rep() functions as appropriate.

1. “a”, “a”, “a”, “a” (2)

rep("a",4)

## [1] "a" "a" "a" "a"

2. The odd numbers in the interval from 1 to 100 (2)

 seq(1,100,by=2)

##  [1]  1  3  5  7  9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45
## [24] 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91
## [47] 93 95 97 99

3. 1, 1, 1, 2, 2, 2, 3, 3, 3 (2)

rep(1:3,each=3)

## [1] 1 1 1 2 2 2 3 3 3

4. 1, 1, 1, 2, 2, 3 (2)

rep(1:3,c(3,2,1))

## [1] 1 1 1 2 2 3

5. 1, 2, 3, 4, 5, 4, 3, 2, 1 (3) Hint: Use the c() function.

c(seq(1,5),seq(4,1))

## [1] 1 2 3 4 5 4 3 2 1

6 Read the monthly precipitation dataset from my website (https://uploads.strikinglycdn.com/files/302190/86f2b03b-8fdc-4df3-aeb7-abf37fc535fe/FLMonthlyP.txt) and create a time series graph of April rainfall for the state. (10)

library (ggplot2)

 loc <- "https://uploads.strikinglycdn.com/files/302190/86f2b03b-8fdc-4df3-aeb7-abf37fc535fe/FLMonthlyP.txt"


Flmp <- read.table(loc,na.string="-9.900",header=TRUE)


ggplot(Flmp,aes(x=Year, y=Apr)) + geom_line() + ylab("April Rainfall in Fl (in)")