Lab 1: Intro to R

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

The graph shows the number of girls baptized over time. The number of girl baptized was increasing starting around 1660 sudden drop after 1700 possibly due to plague occurring at the time.

ggplot(data = arbuthnot, aes(x = year, y = girls)) + 
  geom_line()

Exercise 3

The graph below ilustrates the proportion of boys born over time. The proportion is above the 50% that would be statistically correct as there was more male born than female at that time.

arbuthnot <- arbuthnot %>%
  mutate(total = boys + girls)

arbuthnot <- arbuthnot %>%
  mutate(boy_ratio = boys / total)

ggplot(data = arbuthnot, aes(x = year, y = boy_ratio)) + 
  geom_line()

Exercise 4

Years which are included in the data set are from 1940 through 2002. The dimentions are 3 X 63. The column names are “year,” “boys,” and “girls.”

dim(present)

## [1] 63  3

summary(present)

##       year           boys             girls        
##  Min.   :1940   Min.   :1211684   Min.   :1148715  
##  1st Qu.:1956   1st Qu.:1799857   1st Qu.:1711405  
##  Median :1971   Median :1924868   Median :1831679  
##  Mean   :1971   Mean   :1885600   Mean   :1793915  
##  3rd Qu.:1986   3rd Qu.:2058524   3rd Qu.:1965538  
##  Max.   :2002   Max.   :2186274   Max.   :2082052

Exercise 5

Data from the present data set is significantly higher compare to arbuthnot’s data set. They are not of similar magnitude .

arbuthnot <- arbuthnot %>%
  mutate(total = boys + girls)

present <- present %>%
  mutate(total = boys + girls)

summary( present$total)   

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
## 2360399 3511262 3756547 3679515 4023830 4268326

summary( arbuthnot$total)  

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    5612    9199   11813   11442   14723   16145

Exercise 6

Arbuthnot’s observation about boys being born in greater proportion than girls does not holds up for the U.S. during this time frame. We can see from the grapgh below that the proportion of boys born over time in the present data set is decreased over time.

present <- present %>%
  mutate(total = boys + girls)

present <- present %>%
  mutate(boy_ratio = boys / total)

ggplot(data = present, aes(x = year, y = boy_ratio)) + 
  geom_line()

Exercise 7

1961

present <- present %>% mutate(total = girls + boys)
present %>% arrange(desc(total)) %>% head(1)

## # A tibble: 1 x 5
##    year    boys   girls   total boy_ratio
##   <dbl>   <dbl>   <dbl>   <dbl>     <dbl>
## 1  1961 2186274 2082052 4268326     0.512