Lab report

Load data:

rm(list = ls())
arbuthnot <- read.csv("arbuthnot.csv")

Exercise 1: R,

12 * 7 - 45
## [1] 39
n <- 25
sqrt(n)
## [1] 5

Exercise 2:

scores <- c(88, 92, 79, 95, 84)
length(scores)
## [1] 5
mean(scores)
## [1] 87.6

Exercise 3:

dim(arbuthnot)
## [1] 82  3
names(arbuthnot)
## [1] "year"  "boys"  "girls"
range(arbuthnot$year)
## [1] 1629 1710

Written answer: names; “year, boys, girls”. A single row represents the year and the number of boys and girls baptized in London that year.

Exercise 4:

arbuthnot$girls
##  [1] 4683 4457 4102 4590 4839 4820 4928 4605 4457 4952 4784 5332 5200 4910 4617
## [16] 3997 3919 3395 3536 3181 2746 2722 2840 2908 2959 3179 3349 3382 3289 3013
## [31] 2781 3247 4107 4803 4881 5681 4858 4319 5322 5560 5829 5719 6061 6120 5822
## [46] 5738 5717 5847 6203 6033 6041 6299 6533 6744 7158 7127 7246 7119 7214 7101
## [61] 7167 7302 7392 7316 7483 6647 6713 7229 7767 7626 7452 7061 7514 7656 7683
## [76] 5738 7779 7417 7687 7623 7380 7288
length(arbuthnot$girls)
## [1] 82

Exercise 5:

plot(x = arbuthnot$year, y = arbuthnot$boys, type= "l", main="boys baptized in London, 1692-1710", xlab="year", ylab = "Number of boys baptized", col="steelblue" )

Written answer: In general, the number of boys baptized goes up over time. there is a dip in the 1650s to 60s but it continues to grow to the 1700s

Exercise 6:

proportion_of_boys <- arbuthnot$boys / (arbuthnot$boys + arbuthnot$girls)
plot(x = arbuthnot$year, y = proportion_of_boys, type = "l", main = "Proportion of baptisms that were boys, 1629-1710", xlab = "Year", ylab = "Proportion boys", col = "darkgreen")

Written answer: The proportion fluctuates but it is usually above 0.5. there is usually more boys than girls than girls but a trend is not depicted

Exercise 7:

sum(arbuthnot$girls > arbuthnot$boys)
## [1] 0
arbuthnot$year[which.max(arbuthnot$girls)]
## [1] 1705
arbuthnot$girls[which.max(arbuthnot$girls)]
## [1] 7779

Written answer: No year had more girls than boys. The most girls were baptized in 1705, with 7,779.

On your own:

present <- read.csv("present.csv")

1: [6 pts]

dim(present)
## [1] 63  3
names(present)
## [1] "year"  "boys"  "girls"
range(present$year)
## [1] 1940 2002

Written answer: The present data set has 63 rows and 3 columns (year, boys, girls) covering 1940 to 2002, and each row represents the number of boys and girls born in the United States in a single year

2: [6 pts]

total_present <- present$boys + present$girls
max(total_present)
## [1] 4268326
min(total_present)
## [1] 2360399

Written answer: The largest yearly total is 4,268,326 births in 1961 and the smallest is 2,360,399 births in 1940. Arbuthnot’s yearly totals were only in the thousands so the U.S. totals are hundres of times larger. This is because Arbuthnot only counted baptisms in only one city, London, while the present data counts every recorded birth in the entire U.S. which is a larger population.

3: [8 pts]

plot(x =present$year,y = total_present, type = "l", main = "Total Births In The U.S 1940-2002", xlab = "Year", ylab = "Total Births")

Written answer: Total births rise quickly from about 2.4 million in 1940 to about 4.3 million between 1957 and 1961. It falls thorugh the 1960s and ealry 1970s to a low of about 3.1 million in the mid 1970s. After this the births climb to a second peak of about 4.2 million around 1990. It then is 4 million in 2002. A feature that stands out is the sharp jump right after 1945 when births go from about 2.7 million to 3.7 million in two years. This lines up with the end of World War II and the start of the baby boom.

4: [8 pts]

present$year[which.max(total_present)]
## [1] 1961
total_present[which.max(total_present)]
## [1] 4268326

Written answer: the peak year was 1961 with the total number of births at 4268326 between 1940-2002

5: [12 pts]

prop_present <- present$boys / (present$boys + present$girls)

plot(x = present$year, y = prop_present, type = "l",
     main = "Proportion of U.S. births that were boys, 1940-2002",
     xlab = "Year", ylab = "Proportion boys")

sum(present$boys > present$girls)
## [1] 63

Written answer: boys outnumber the girls in all 63 years, so Arbuthnots observation is true in the modern US during this time frame. The proportion is highest in the 40s, drifts down with some bumbs, and lowest around 2000; although the drop is quite small.

Teamwork report

Team member Attendance Author Contribution %
Angel Obike Yes / No Yes / No
Katie Huang Yes / No Yes / No
Aleah Saunders Yes / No Yes / No
Name of member 4 Yes / No Yes / No
Name of member 5 Yes / No Yes / No
Total 100%