library(tidyverse)
library(openintro)

Exercise 1

arbuthnot$girls
##  [1] 4683 4457 4102 4590 4839 4820 4928 4605 4457 4952 4784 5332 5200 4910 4617
## [16] 3997 3919 3395 3536 3181 2746 2722 2840 2908 2959 3179 3349 3382 3289 3013
## [31] 2781 3247 4107 4803 4881 5681 4858 4319 5322 5560 5829 5719 6061 6120 5822
## [46] 5738 5717 5847 6203 6033 6041 6299 6533 6744 7158 7127 7246 7119 7214 7101
## [61] 7167 7302 7392 7316 7483 6647 6713 7229 7767 7626 7452 7061 7514 7656 7683
## [76] 5738 7779 7417 7687 7623 7380 7288

Exercise 2

Insert any text here.

# Insert code for Exercise 2 here
ggplot(data=arbuthnot, aes(x=year, y=girls))+geom_point()

Exercise 3

Insert any text here.

# Insert code for Exercise 3 here
arbuthnot<-arbuthnot%>%mutate(total=boys+girls)
arbuthnot<-arbuthnot%>%mutate(boy_ratio=boys/total)
ggplot(data=arbuthnot, aes(x=year, y=boy_ratio))+geom_point()

Exercise 4

Insert any text here.

# Insert code for Exercise 4 here
glimpse(present)
## Rows: 63
## Columns: 3
## $ year  <dbl> 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950~
## $ boys  <dbl> 1211684, 1289734, 1444365, 1508959, 1435301, 1404587, 1691220, 1~
## $ girls <dbl> 1148715, 1223693, 1364631, 1427901, 1359499, 1330869, 1597452, 1~

Exercise 5

Insert any text here.

# Insert code for Exercise 5 here
present<-present%>%mutate(compare=boys>girls)

Exercise 6

Insert any text here.

# Insert code for Exercise 6 here
ggplot(data=present, aes(x=year, y=boys))+geom_point()

Exercise 7

Insert any text here.

# Insert code for Exercise 7 here
present<-present%>%mutate(total=boys+girls)
present%>%summarize(max=max(total))
## # A tibble: 1 x 1
##       max
##     <dbl>
## 1 4268326
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