Lab 1: Intro to R

library(tidyverse)
library(openintro)

Exercise 1

length(arbuthnot$girls)

## [1] 82

Exercise 2

I found a increase linear regression trend, and the number of girls baptized increasing over the years.

ggplot(data = arbuthnot, aes(x=year, y=girls)) + 
  geom_point() +
  stat_smooth(method="lm", col= "red")

## `geom_smooth()` using formula 'y ~ x'

Exercise 3

I found a decreased linear regression trend, and the boy’s ratio decreased over the years.

total <- arbuthnot$boys + arbuthnot$girls

ggplot(data = arbuthnot, aes(x=year, y=boys/total)) + 
  geom_line() +
  stat_smooth(method="lm", col= "red")

## `geom_smooth()` using formula 'y ~ x'

Exercise 4

Year 1940 ~ 2002 63 rows 3 columns 3 variable : year, boys, girls

present$year

##  [1] 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949 1950 1951 1952 1953 1954
## [16] 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969
## [31] 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984
## [46] 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
## [61] 2000 2001 2002

dim(present)

## [1] 63  3

names(present)

## [1] "year"  "boys"  "girls"

Exercise 5

arbuthnot > present, their not similar magnitude.

length(total)

## [1] 82

length(present$girls + present$boys)

## [1] 63

Exercise 6

I found a decreased linear regression trend, and the boy’s ratio decreased over the years in US.

total <- present$boys + present$girls

ggplot(data = present, aes(x=year, y=boys/total)) + 
  geom_line() +
  stat_smooth(method="lm", col= "red")

## `geom_smooth()` using formula 'y ~ x'

Exercise 7

Year 1961

present$year[which.max(present$boys +present$girls)]

## [1] 1961

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

present %>%
  arrange(desc(total))

## # A tibble: 63 × 4
##     year    boys   girls   total
##    <dbl>   <dbl>   <dbl>   <dbl>
##  1  1961 2186274 2082052 4268326
##  2  1960 2179708 2078142 4257850
##  3  1957 2179960 2074824 4254784
##  4  1959 2173638 2071158 4244796
##  5  1958 2152546 2051266 4203812
##  6  1962 2132466 2034896 4167362
##  7  1956 2133588 2029502 4163090
##  8  1990 2129495 2028717 4158212
##  9  1991 2101518 2009389 4110907
## 10  1963 2101632 1996388 4098020
## # … with 53 more rows