This document discusses analyzing name usage data from a dataset containing boy and girl name usage over time. It uses the plyr package to summarize a subset of names that are used for both boys and girls, looking at the number of years each name has been used and its average usage. Graphs are created to examine patterns in the log ratio of boy to girl usage for selected names over 50 years that had average usage over 0.0005. The analysis aims to understand how usage of these unisex names has changed over time and to potentially estimate error rates in the data.

1. Stat405 ddply case study (2)
Hadley Wickham
Thursday, 7 October 2010

2. 1. Recap
1. Focus on smaller subset
2. More ddply
1. Develop summary statistic
2. Classify names
3. Apply to full data
Thursday, 7 October 2010

3. Questions
For names that are used for both boys
and girls, how has usage changed?
Can we use names that clearly have the
incorrect sex to estimate error rates over
time?
Thursday, 7 October 2010

4. Getting started
options(stringsAsFactors = FALSE)
library(plyr)
library(ggplot2)
both <- read.csv("both.csv")
Thursday, 7 October 2010

5. Interesting subset
both_sum <- ddply(both, "name", summarise,
years = length(name),
avg_usage = mean(boy + girl) / 2
)
both_sum <- subset(both_sum, years > 1)
qplot(years, avg_usage, data = both_sum)
selected_names <- subset(both_sum,
years > 50 & avg_usage > 0.0005)$name
selected <- subset(both, name %in% selected_names)
Thursday, 7 October 2010

6. Patterns
selected$lratio <- with(selected,
log10(boy / girl))
qplot(lratio, name, data = selected)
qplot(lratio, reorder(name, lratio),
data = selected)
qplot(abs(lratio), reorder(name, lratio),
data = selected)
Thursday, 7 October 2010

7. Richard ●●●● ●●●● ● ●●● ●●●●●
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William ●● ●● ●●●●●●●● ●●● ●●●
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Thomas ● ● ●● ●●●●●● ● ● ● ●
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David ●●● ●●●●●●● ●●●●● ●●● ● ●
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John ●●●●●●● ●●●●●●●●● ●
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Robert ●●● ● ● ●● ●●●● ●● ● ● ●
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James ●●●● ● ●●●●● ●●●●●● ●
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Joseph ●●●●● ●●●●●●●●●●●
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Frank ● ● ●● ●●●●●● ●●●●
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Charles ● ●●● ●●●●●●●●●●●●
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Michael ●●●● ●●●●●●● ●●● ● ●
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George ● ●●●●●●●●●●●●●●
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Henry ●●●●● ●●●● ●● ● ● ●●
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Joe ●●●● ●●●● ●●●● ●● ● ●
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Jesse ● ● ● ●●●●● ●● ●●●● ●● ● ● ●● ●
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Charlie ●● ● ● ●●●●● ● ●●● ●●●● ●● ●● ●● ● ●● ●
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Ray ● ●● ●●●● ●● ● ● ● ● ●●
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Jerry ●● ● ● ● ●● ● ● ●●● ●●●● ●●● ● ●●
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Clyde ●●●●●●● ●●●● ●●●●● ●
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Dale ● ● ●● ● ● ● ●● ●●●● ●● ● ● ● ● ● ●
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Ira ●●●●●●●●● ● ● ● ● ●
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Francis ●●● ●●●●● ●●● ● ● ●
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Eddie ●●●●●●●●●●●●
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Cecil ● ● ● ● ●● ● ●● ●●● ●● ● ● ● ●● ●●● ●
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Gene ● ●● ● ● ● ●●●●●●●
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Sidney ●●● ●● ● ● ●●●●
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reorder(name, lratio)
Lee ●●● ●●● ●●●● ●●●●● ● ● ●●● ●● ●
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Terry ● ●● ●● ●●● ● ● ●●●● ●● ● ● ●●●●
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Willie ●●●●●●●●●●●● ● ● ●● ● ● ●●● ●●
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Jimmie ●●● ●● ●● ●●● ●●●●●●●● ●● ●
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Johnnie ●●●●●●●●●● ●●● ●
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Leslie ●●
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Angel ●●● ●●●●●● ● ● ● ●● ●●
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Jackie ●● ● ●●●●●● ● ● ●
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Jessie ●●●●●●●●●● ●●● ● ●●● ●
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Lynn ●● ● ● ●● ●●● ●●●● ● ● ●●●●●●●
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Marion ● ●●● ●●●● ●●●● ●
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Dana ●●●●●● ●●●●●
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Ollie ●● ●●● ●●●●●●●●●●
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Tracy ● ●●●●●● ●● ● ● ●●●● ●● ● ● ● ●● ● ●
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Billie ●● ●●●●●●●●●● ● ● ●●●●● ● ●● ●●
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Jamie ● ● ● ● ●● ● ● ● ● ●●●●●● ●●
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Gail ●●●●●● ●●●● ● ●
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Robin ● ●● ● ●●●
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Patsy ●●● ●●● ●●●
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Kelly ● ● ●● ● ●●● ●●● ● ● ●
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Ora ●●●● ●●● ●●●●●● ● ●
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Shannon ● ● ●●● ●●● ●●●●● ● ● ● ● ●●● ●
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Connie ● ●●●● ●●●● ● ●●●●● ● ● ●●● ● ● ● ●● ● ● ● ● ● ● ● ●●● ● ●●
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Jean ● ●●●●● ● ● ● ● ● ●●●● ● ● ●● ● ● ●●● ● ● ●●● ●●●●●●● ●
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Shirley ● ●● ● ● ● ●● ●
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June ● ●● ● ●● ●● ● ●● ● ●
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Bonnie ●● ● ●●●●● ●●● ● ●●● ● ●
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Pearl ● ● ●● ● ●●● ●●●● ● ● ●
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Carol ● ● ●● ● ● ●
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Bernice ● ● ● ● ● ● ●●●●●●● ● ●
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Ruby ● ● ●● ● ● ●●● ●● ●● ●● ●●
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Hazel ●● ● ●●●●●●● ●
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Frances ● ●● ●● ●●●●● ●●●●● ●●
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Elizabeth ● ●● ●●●●●●●● ● ● ●
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Margaret ● ●● ●●●●●●●●● ● ● ● ●
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Helen ● ●● ● ●● ● ● ● ●●● ● ●●
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Mary ●●● ●●●●●●●● ● ●●●●● ●
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0.5 1.0 1.5 2.0 2.5
Thursday, 7 October 2010 abs(lratio)

8. Richard ●●●● ●●●● ● ●●● ●●●●●
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William ●● ●● ●●●●●●●● ●●● ●●●
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Thomas ● ● ●● ●●●●●● ● ● ● ●
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David ●●● ●●●●●●● ●●●●● ●●● ● ●
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John ●●●●●●● ●●●●●●●●● ●
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●●●● ●● ● ●●● ● ●●
● ● ● ●● ● ● ● ●●●
● ● ●●
●●
●● ●
Robert ●●● ● ● ●● ●●●● ●● ● ● ●
● ●●●● ●●●●●●●●●
●● ● ●● ●●●●● ●● ●
● ● ● ●● ●●●●
●● ● ●
● ● ●●
James ●●●● ● ●●●●● ●●●●●● ●
●●●● ●●●●●● ●● ●●●
●● ● ●● ●●●●●● ●●
●● ● ●●● ●●● ●
●●●
● ●● ● ●● ●
●● ●●
●
Joseph ●●●●● ●●●●●●●●●●●
● ●●● ●●●●●●●● ●●
●●● ●● ● ●● ● ●● ●●
●●●● ● ●●● ●
● ●● ●
Frank ● ● ●● ●●●●●● ●●●●
● ●●● ●● ●●●
● ● ●●● ● ● ●
●● ●
● ●
Charles ● ●●● ●●●●●●●●●●●●
●● ● ●● ●●●● ●● ●●●
● ●● ●●●● ●●
● ● ●●●● ●
●●●●●
●● ● ●
Michael ●●●● ●●●●●●● ●●● ● ●
●●● ●●● ●●● ● ● ●
●●● ● ● ●
●● ● ● ●●
George ● ●●●●●●●●●●●●●●
●●●●●●● ● ●●●
● ●●●● ● ● ● ●
● ●● ●
●● ●● ● ●●●
● ●●
●●
Henry ●●●●● ●●●● ●● ● ● ●●
●●●● ●● ●●●● ● ●
●●●● ● ● ●● ● ● ●
● ● ● ●●●
●● ●
Joe ●●●● ●●●● ●●●● ●● ● ●
●●●● ●●●● ● ● ●●
●●●● ●●●● ●● ●●● ●
●●●
●●● ●●●●●
●
●
● ●●
Jesse ● ● ● ●●●●● ●● ●●●● ●● ● ● ●● ●
● ●● ●
● ●●
●● ●● ● ●● ● ●
● ●
Charlie ●● ● ● ●●●●● ● ●●● ●●●● ●● ●● ●● ● ●● ●
●● ●
●● ●●● ● ●
●●●
● ●●
● ● ● ●●● ● ● ●● ● ●●
●
●●
Ray ● ●● ●●●● ●● ● ● ● ● ●●
●● ●●●● ●● ●● ● ●●
●● ● ●
●● ●
● ●●
Jerry ●● ● ● ● ●● ● ● ●●● ●●●● ●●● ● ●●
●● ● ● ●● ●● ●●● ●● ●●● ● ● ●
● ● ● ●● ●● ●
●
Clyde ●●●●●●● ●●●● ●●●●● ●
● ● ●●● ● ●● ● ●● ●
● ●● ●
● ● ●●●
Dale ● ● ●● ● ● ● ●● ●●●● ●● ● ● ● ● ● ●
●● ● ● ●●● ●●● ● ●● ●●● ●●
●● ●
●● ●●
●● ● ● ●
●●
●
Ira ●●●●●●●●● ● ● ● ● ●
● ● ●●● ●●● ●●
● ●●● ● ● ●
●●● ● ●
●●
Francis ●●● ●●●●● ●●● ● ● ●
●●● ● ●●●●● ●●●●
●● ● ●●●●●● ●●
●● ●●●●●● ●
●●●● ●
●● ●●
Eddie ●●●●●●●●●●●●
●● ●● ●●●●●●●
● ● ●● ●●● ●● ●●● ● ● ● ●
● ● ● ●●
●●●
●●
● ●● ● ● ●
●
Cecil ● ● ● ● ●● ● ●● ●●● ●● ● ● ● ●● ●●● ●
● ● ● ● ●● ●
●● ●● ●●● ●
●●● ● ●●●●●
● ●●●●
●●●
Gene ● ●● ● ● ● ●●●●●●●
● ● ● ●●●●●●
● ● ●● ●● ● ●● ● ● ● ●●● ● ● ●●● ●
● ●● ●●
●● ●●
●
Sidney ●●● ●● ● ● ●●●●
● ●●● ● ●●● ● ●● ●●● ●● ●● ●● ●
●●● ● ● ● ●●● ● ● ●
●● ●
● ● ●●● ● ●
● ● ●
reorder(name, lratio)
What characteristics
Lee ●●● ●●● ●●●● ●●●●● ● ● ●●● ●● ●
●● ●●● ●● ●● ●●●●●● ● ●●● ●
●●●
●●● ●● ●● ●● ●●● ● ●●● ●
●● ● ●●●●
● ● ●● ● ●
● ● ●
●●
Terry ● ●● ●● ●●● ● ● ●●●● ●● ● ● ●●●●
● ●● ●● ●● ●● ●● ● ● ●● ● ● ●
● ● ● ● ● ● ●● ●
● ●● ● ●
● ●● ●●
Willie ●●●●●●●●●●●● ● ● ●● ● ● ●●● ●●
●●●●●●● ●● ●● ● ● ●●●●
● ● ● ●●●
● ● ●●●●
●
● ●●
●●
● ●
● ● ●
Jimmie ●●● ●● ●● ●●● ●●●●●●●● ●● ●
●●● ●
●●● ● ● ●●● ● ●●● ●● ● ●
●●●● ●● ●● ●● ●
●●
●●
●● ●●
●● ●
●●
separate sex-errors
Johnnie ●●●●●●●●●● ●●● ●
●●● ●●●●●● ● ●●
●●●●●●●●●●●
●●●● ● ● ●●
●●● ● ●● ●●
●●● ● ●
●
Leslie ●●
●●
● ● ●●
● ●
● ●● ● ●●●
● ● ● ● ●● ●●●●●●●● ●●●●● ●
● ● ●● ●●●●● ● ●●●●●
● ● ●●● ●● ●●●●● ●
●●●●
●● ● ●● ●
●● ●●
Angel ●●● ●●●●●● ● ● ● ●● ●●
●●● ●●●●● ● ●
● ● ●● ●● ●
● ●● ●
● ● ●● ● ● ●
Jackie ●● ● ●●●●●● ● ● ●
●● ●●●●●●● ● ● ●
● ● ●●●●● ●●
●● ●● ●●
●● ●●
●●● ●
from dual-sex names?
Jessie ●●●●●●●●●● ●●● ● ●●● ●
●●●●●● ●●●●●● ● ● ● ●
●● ●● ●●●●●● ●
●● ●●●● ● ●●
●● ● ●● ●●●●
●●
●●
●
● ● ●●● ●
Lynn ●● ● ● ●● ●●● ●●●● ● ● ●●●●●●●
●● ● ●● ● ●● ● ●● ● ●●●●● ●
● ● ● ● ● ●●●●
● ● ●●● ●●
● ● ●●
Marion ● ●●● ●●●● ●●●● ●
● ●●● ●●●● ●●●●
● ● ● ●●● ●●●●
● ●●
● ● ●●
● ● ●●
●●●
●●
●
Dana ●●●●●● ●●●●●
● ●● ●● ●● ●
●● ●● ●●●
●●●●● ●● ●
● ● ● ● ●● ● ●● ●● ● ●
●● ●●●● ●
● ● ● ●● ●●
●
●
Ollie ●● ●●● ●●●●●●●●●●
●● ● ●●●●●●● ●
●● ●●●●●●
● ●●●● ●
●●●
●●●
●●
●
Tracy ● ●●●●●● ●● ● ● ●●●● ●● ● ● ● ●● ● ●
● ● ●●● ●●● ●
● ●● ●● ●
● ● ● ●● ●●
●● ● ● ●●
● ●●●
Billie ●● ●●●●●●●●●● ● ● ●●●●● ● ●● ●●
● ● ● ●●●● ●●● ● ●● ● ● ●● ●
● ●●● ● ●●
● ● ●● ● ●
● ●●
●● ●● ● ● ●
● ●●●
●● ●
Jamie ● ● ● ● ●● ● ● ● ● ●●●●●● ●●
● ●● ● ● ● ● ● ● ● ●●● ●●● ●
● ● ● ●
● ● ● ●●●
● ● ●●●● ●●
● ●
●
Gail ●●●●●● ●●●● ● ●
●●●● ●● ● ●
●● ● ●
● ● ●●
● ● ● ● ● ●● ●● ● ● ●●
● ● ● ● ● ●●● ● ●
●●● ●
Robin ● ●● ● ●●●
● ● ●● ●●●● ● ● ● ●● ● ●●●●● ●
● ●●
●●● ●● ● ●● ● ●●●
●● ●
●● ●● ●
●●
Patsy ●●● ●●● ●●●
● ● ● ●●●●
●
● ● ●● ● ● ● ● ●● ●● ● ● ● ● ●● ● ●
● ●● ●● ● ●
Kelly ● ● ●● ● ●●● ●●● ● ● ●
● ● ●● ●
●●● ●● ● ● ●●●●● ●
● ●●●●●●
●●● ●
●● ●●
●
Ora ●●●● ●●● ●●●●●● ● ●
● ● ●● ●●●●● ●
● ●● ●●●●●
●●● ●● ●
● ●●
●
Shannon ● ● ●●● ●●● ●●●●● ● ● ● ● ●●● ●
● ●● ●● ●● ●● ● ● ● ● ●●
● ●● ● ● ●
● ● ● ● ● ●●
●
Connie ● ●●●● ●●●● ● ●●●●● ● ● ●●● ● ● ● ●● ● ● ● ● ● ● ● ●●● ● ●●
● ● ● ●●● ●● ●●● ● ● ● ● ● ● ●
● ●● ● ● ●● ● ● ●● ●● ● ●
Jean ● ●●●●● ● ● ● ● ● ●●●● ● ● ●● ● ● ●●● ● ● ●●● ●●●●●●● ●
● ● ● ● ●●● ● ● ● ● ● ●
● ● ● ● ●●● ● ● ● ●● ●● ●●●●
●
●
●●
●● ●●●● ●●
●● ● ●
●
Shirley ● ●● ● ● ● ●● ●
●● ●● ● ●● ●
● ●● ●● ● ●●●
●●● ● ● ● ●● ● ● ● ● ● ●● ● ●● ● ● ● ● ●●● ●
● ●● ●●●
●●
● ● ● ●● ●
June ● ●● ● ●● ●● ● ●● ● ●
● ● ●● ● ●
●● ●● ● ● ●● ● ● ● ●●● ●●●●
● ●● ●●●
● ●
Bonnie ●● ● ●●●●● ●●● ● ●●● ● ●
●●●●● ● ● ●● ●
● ● ● ● ●●● ● ● ● ●
● ● ●
● ●● ● ● ●● ●●●●
● ●●● ●
Pearl ● ● ●● ● ●●● ●●●● ● ● ●
●●●
● ●● ●● ● ● ●●●● ●
●● ● ●●● ● ●
●● ●
● ●●
Carol ● ● ●● ● ● ●
● ● ● ●●● ●● ● ●
● ● ●●
● ● ● ● ● ● ●
● ● ● ● ●●● ● ● ● ●● ● ● ●●
● ● ● ●● ●
●●● ●
●
Bernice ● ● ● ● ● ● ●●●●●●● ● ●
● ●●● ● ●●●● ● ●
● ● ●●●●● ●
●●
●●●
●●
Ruby ● ● ●● ● ● ●●● ●● ●● ●● ●●
●● ● ●● ● ● ● ●● ●
● ● ● ● ●● ●
●● ● ●
Hazel ●● ● ●●●●●●● ●
● ● ●●● ●●●●
● ● ●● ●●●●
● ● ●● ●
●
Frances ● ●● ●● ●●●●● ●●●●● ●●
● ● ●●●● ●● ● ● ●● ●
●● ● ● ● ● ● ●
●●
● ● ●●●
●
Elizabeth ● ●● ●●●●●●●● ● ● ●
●●●● ● ●●●● ● ●
● ●● ●●●●● ●
● ●●
●
Margaret ● ●● ●●●●●●●●● ● ● ● ●
● ●● ●●●●● ●● ● ● ●
● ● ● ●●● ●●
● ●● ● ●
Helen ● ●● ● ●● ● ● ● ●●● ● ●●
● ● ●● ●●● ●● ●● ● ● ●
● ●● ● ●●●● ●
Mary ●●● ●●●●●●●● ● ●●●●● ●
●●● ● ●●●●●●● ●●●●● ●
●●● ● ●●● ● ● ●●● ● ●
● ●●● ● ●●●
●● ●
● ●● ●●
0.5 1.0 1.5 2.0 2.5
Thursday, 7 October 2010 abs(lratio)

9. Your turn
Compute the mean and range of lratio for
each name.
Plot and come up with cutoffs that you
think separate the two groups.
Thursday, 7 October 2010

10. rng <- ddply(selected, "name", summarise,
diff = diff(range(lratio, na.rm = T)),
mean = mean(lratio, na.rm = T)
)
qplot(diff, abs(mean), data = rng)
qplot(diff, abs(mean), data = rng, geom = "text",
label = name)
rng$dual <- abs(rng$mean) < 2
arrange(rng, mean, dual)
selected <- join(selected, rng[c("name", "dual")])
Thursday, 7 October 2010

11. Richard
William
Thomas
David
John
Robert
James
Joseph
FrankMary
Charles
Helen
Margaret
Michael
Elizabeth
George
Henry
2.0
Frances
Hazel
Ruby
Joe
Jesse
Bernice Carol
1.5
Pearl Charlie
Ray
abs(mean)
Clyde Jerry Bonnie
Dale June Shirley
Ira Jean
1.0 Francis Eddie
Cecil Gene Connie
Sidney
Ora Shannon
Lee Kelly Gail
Patsy
Terry Robin
0.5
Willie
Jimmie
Jamie Billie
Johnnie
Ollie Tracy
Marion Dana Leslie
Angel Lynn
Jessie
Jackie
0.5 1.0 1.5 2.0 2.5
diff
Thursday, 7 October 2010

12. Richard
William
Thomas
John
Joseph
FrankDavid
Robert
JamesMary
Charles
Helen
Margaret Why does this pattern
Michael
Elizabeth
George
Henry give us confidence
2.0 that those dual-sex
Frances
Hazel
Ruby
names are errors?
Joe
Jesse
Bernice Carol
1.5
Pearl Charlie
Ray
abs(mean)
Clyde Jerry Bonnie
Dale June Shirley
Ira Jean
1.0 Francis Eddie
Cecil Gene Connie
Sidney
Ora Shannon
Lee Kelly Gail
Patsy
Terry Robin
0.5
Willie
Jimmie
Jamie Billie
Johnnie
Ollie Tracy
Marion Dana Leslie
Angel Lynn
Jessie
Jackie
0.5 1.0 1.5 2.0 2.5
diff
Thursday, 7 October 2010

13. qplot(year, lratio, data = selected, geom = "line",
group = name) + facet_wrap(~ dual)
qplot(year, lratio, data = subset(selected, dual),
geom = "line") + facet_wrap(~ name)
qplot(year, boy / (boy + girl),
data = subset(selected, dual), geom = "line") +
facet_wrap(~ name)
Thursday, 7 October 2010

14. Your turn
Apply this threshold to all names, not just
the few we focussed in on. Does it still
seem like a good classification?
What can you say about trends in errors
over time?
Thursday, 7 October 2010

15. both$lratio <- with(both, log10(boy / girl))
rng <- ddply(both, "name", summarise,
diff = diff(range(lratio, na.rm = T)),
mean = mean(lratio, na.rm = T)
)
rng$dual <- abs(rng$mean) < 2
arrange(rng, mean, dual)
both <- join(both, rng[c("name", "dual")])
qplot(year, lratio, data = subset(both, !dual))
qplot(year, abs(lratio), data = subset(both, !dual),
colour = factor(boy > girl)) +
geom_smooth(size = 3)
Thursday, 7 October 2010

16. Math on the
computer
Thursday, 7 October 2010

17. Your turn
Perform the following calculations in R.
Are the answers what you expect?
seq(0.1, 0.9, by = 0.1) - 1:9 / 10
sqrt(2)^2 - 2
What is the property of these numbers
that might cause the problem?
Thursday, 7 October 2010

18. # Each number must be stored in a finite amount of space
# => each number can only have a finite number of digits
# => floating point math does not work like normal math
(1e-16 + 1) == 1
(1e-16 + 1) * 10 == 1e-16 * 10 + 1 * 10
1e9 + 2 - 0.1 - 1e9
1e10 + 2 - 0.1 - 1e10
1e11 + 2 - 0.1 - 1e11
1e12 + 2 - 0.1 - 1e12
1e13 + 2 - 0.1 - 1e13
1e14 + 2 - 0.1 - 1e14
Thursday, 7 October 2010

19. a⋅(b + c) = a⋅b + a⋅c
a + (b + c) = (a + b) + c
a+b-b=a
Thursday, 7 October 2010

20. # By default R only shows 7 significant digits
# If the trailing digits are zero, the number will be rounded
(1 / 237)
(1 / 237) * 237
(1 / 237) * 237 - 1
seq(0.1, 0.9, by = 0.1)
seq(0.1, 0.9, by = 0.1) - 1:9 / 10
# Tricky to get to print exactly:
formatC((1 / 237) * 237, digits = 20)
formatC(seq(0.1, 0.9, by = 0.1), digits = 20)
Thursday, 7 October 2010

21. # When working with floating point numbers (numeric)
# (but not integers, this is the one place where the
# difference is important) never test for equality with ==
a <- seq(0.1, 0.9, by = 0.1)
b <- 1:9 / 10
all(a == b)
all.equal(a, b)
all(abs(a - b) < 1e-6)
# Similarly, need to be careful with < and > etc
Thursday, 7 October 2010

22. # Places where this matters:
#
# * sums
# * calculating the standard deviation
# * inverting a matrix (condition)
# * linear models!
# * maximum likelihood estimation
Thursday, 7 October 2010

23. Homework
Reflection on project teams.
Plyr drills.
Plyr practice with basketball data (what
we’ll be using for the next project).
Thursday, 7 October 2010