Peter Ralph
21 January 2020 – Advanced Biological Statistics
HairEyeColor package:datasets R Documentation
Hair and Eye Color of Statistics Students
Description:
Distribution of hair and eye color and sex in 592 statistics
students.
Usage:
HairEyeColor
Format:
A 3-dimensional array resulting from cross-tabulating 592
observations on 3 variables. The variables and their levels are
as follows:
No Name Levels
1 Hair Black, Brown, Red, Blond
2 Eye Brown, Blue, Hazel, Green
3 Sex Male, Female
Details:
The Hair x Eye table comes from a survey of students at the
University of Delaware reported by Snee (1974). The split by
‘Sex’ was added by Friendly (1992a) for didactic purposes.
This data set is useful for illustrating various techniques for
the analysis of contingency tables, such as the standard
chi-squared test or, more generally, log-linear modelling, and
graphical methods such as mosaic plots, sieve diagrams or
association plots.
Source:
<URL:
http://euclid.psych.yorku.ca/ftp/sas/vcd/catdata/haireye.sas>
Snee (1974) gives the two-way table aggregated over ‘Sex’. The
‘Sex’ split of the ‘Brown hair, Brown eye’ cell was changed to
agree with that used by Friendly (2000).
References:
Snee, R. D. (1974). Graphical display of two-way contingency
tables. _The American Statistician_, *28*, 9-12. doi:
10.2307/2683520 (URL: http://doi.org/10.2307/2683520).
## , , Sex = Male
##
## Eye
## Hair Brown Blue Hazel Green
## Black 32 11 10 3
## Brown 53 50 25 15
## Red 10 10 7 7
## Blond 3 30 5 8
##
## , , Sex = Female
##
## Eye
## Hair Brown Blue Hazel Green
## Black 36 9 5 2
## Brown 66 34 29 14
## Red 16 7 7 7
## Blond 4 64 5 8
haireye <- as.data.frame(HairEyeColor)
names(haireye) <- tolower(names(haireye))
names(haireye)[names(haireye) == "freq"] <- "number"
haireye
## hair eye sex number
## 1 Black Brown Male 32
## 2 Brown Brown Male 53
## 3 Red Brown Male 10
## 4 Blond Brown Male 3
## 5 Black Blue Male 11
## 6 Brown Blue Male 50
## 7 Red Blue Male 10
## 8 Blond Blue Male 30
## 9 Black Hazel Male 10
## 10 Brown Hazel Male 25
## 11 Red Hazel Male 7
## 12 Blond Hazel Male 5
## 13 Black Green Male 3
## 14 Brown Green Male 15
## 15 Red Green Male 7
## 16 Blond Green Male 8
## 17 Black Brown Female 36
## 18 Brown Brown Female 66
## 19 Red Brown Female 16
## 20 Blond Brown Female 4
## 21 Black Blue Female 9
## 22 Brown Blue Female 34
## 23 Red Blue Female 7
## 24 Blond Blue Female 64
## 25 Black Hazel Female 5
## 26 Brown Hazel Female 29
## 27 Red Hazel Female 7
## 28 Blond Hazel Female 5
## 29 Black Green Female 2
## 30 Brown Green Female 14
## 31 Red Green Female 7
## 32 Blond Green Female 8
Questions:
… is the probability of seeing something at least as extreme as what we saw in the data, if the null hypothesis (model) is true.
A permutation test estimates the “probability … under the null hypothesis” part.
First, “individualize” the data:
long_haireye <- haireye[rep(1:nrow(haireye), haireye$number),
c("hair", "eye", "sex")]
stopifnot(nrow(long_haireye) == sum(haireye$number))
long_haireye
## hair eye sex
## 1 Black Brown Male
## 1.1 Black Brown Male
## 1.2 Black Brown Male
## 1.3 Black Brown Male
## 1.4 Black Brown Male
## 1.5 Black Brown Male
## 1.6 Black Brown Male
## 1.7 Black Brown Male
## 1.8 Black Brown Male
## 1.9 Black Brown Male
## 1.10 Black Brown Male
## 1.11 Black Brown Male
## 1.12 Black Brown Male
## 1.13 Black Brown Male
## 1.14 Black Brown Male
## 1.15 Black Brown Male
## 1.16 Black Brown Male
## 1.17 Black Brown Male
## 1.18 Black Brown Male
## 1.19 Black Brown Male
## 1.20 Black Brown Male
## 1.21 Black Brown Male
## 1.22 Black Brown Male
## 1.23 Black Brown Male
## 1.24 Black Brown Male
## 1.25 Black Brown Male
## 1.26 Black Brown Male
## 1.27 Black Brown Male
## 1.28 Black Brown Male
## 1.29 Black Brown Male
## 1.30 Black Brown Male
## 1.31 Black Brown Male
## 2 Brown Brown Male
## 2.1 Brown Brown Male
## 2.2 Brown Brown Male
## 2.3 Brown Brown Male
## 2.4 Brown Brown Male
## 2.5 Brown Brown Male
## 2.6 Brown Brown Male
## 2.7 Brown Brown Male
## 2.8 Brown Brown Male
## 2.9 Brown Brown Male
## 2.10 Brown Brown Male
## 2.11 Brown Brown Male
## 2.12 Brown Brown Male
## 2.13 Brown Brown Male
## 2.14 Brown Brown Male
## 2.15 Brown Brown Male
## 2.16 Brown Brown Male
## 2.17 Brown Brown Male
## 2.18 Brown Brown Male
## 2.19 Brown Brown Male
## 2.20 Brown Brown Male
## 2.21 Brown Brown Male
## 2.22 Brown Brown Male
## 2.23 Brown Brown Male
## 2.24 Brown Brown Male
## 2.25 Brown Brown Male
## 2.26 Brown Brown Male
## 2.27 Brown Brown Male
## 2.28 Brown Brown Male
## 2.29 Brown Brown Male
## 2.30 Brown Brown Male
## 2.31 Brown Brown Male
## 2.32 Brown Brown Male
## 2.33 Brown Brown Male
## 2.34 Brown Brown Male
## 2.35 Brown Brown Male
## 2.36 Brown Brown Male
## 2.37 Brown Brown Male
## 2.38 Brown Brown Male
## 2.39 Brown Brown Male
## 2.40 Brown Brown Male
## 2.41 Brown Brown Male
## 2.42 Brown Brown Male
## 2.43 Brown Brown Male
## 2.44 Brown Brown Male
## 2.45 Brown Brown Male
## 2.46 Brown Brown Male
## 2.47 Brown Brown Male
## 2.48 Brown Brown Male
## 2.49 Brown Brown Male
## 2.50 Brown Brown Male
## 2.51 Brown Brown Male
## 2.52 Brown Brown Male
## 3 Red Brown Male
## 3.1 Red Brown Male
## 3.2 Red Brown Male
## 3.3 Red Brown Male
## 3.4 Red Brown Male
## 3.5 Red Brown Male
## 3.6 Red Brown Male
## 3.7 Red Brown Male
## 3.8 Red Brown Male
## 3.9 Red Brown Male
## 4 Blond Brown Male
## 4.1 Blond Brown Male
## 4.2 Blond Brown Male
## 5 Black Blue Male
## 5.1 Black Blue Male
## 5.2 Black Blue Male
## 5.3 Black Blue Male
## 5.4 Black Blue Male
## 5.5 Black Blue Male
## 5.6 Black Blue Male
## 5.7 Black Blue Male
## 5.8 Black Blue Male
## 5.9 Black Blue Male
## 5.10 Black Blue Male
## 6 Brown Blue Male
## 6.1 Brown Blue Male
## 6.2 Brown Blue Male
## 6.3 Brown Blue Male
## 6.4 Brown Blue Male
## 6.5 Brown Blue Male
## 6.6 Brown Blue Male
## 6.7 Brown Blue Male
## 6.8 Brown Blue Male
## 6.9 Brown Blue Male
## 6.10 Brown Blue Male
## 6.11 Brown Blue Male
## 6.12 Brown Blue Male
## 6.13 Brown Blue Male
## 6.14 Brown Blue Male
## 6.15 Brown Blue Male
## 6.16 Brown Blue Male
## 6.17 Brown Blue Male
## 6.18 Brown Blue Male
## 6.19 Brown Blue Male
## 6.20 Brown Blue Male
## 6.21 Brown Blue Male
## 6.22 Brown Blue Male
## 6.23 Brown Blue Male
## 6.24 Brown Blue Male
## 6.25 Brown Blue Male
## 6.26 Brown Blue Male
## 6.27 Brown Blue Male
## 6.28 Brown Blue Male
## 6.29 Brown Blue Male
## 6.30 Brown Blue Male
## 6.31 Brown Blue Male
## 6.32 Brown Blue Male
## 6.33 Brown Blue Male
## 6.34 Brown Blue Male
## 6.35 Brown Blue Male
## 6.36 Brown Blue Male
## 6.37 Brown Blue Male
## 6.38 Brown Blue Male
## 6.39 Brown Blue Male
## 6.40 Brown Blue Male
## 6.41 Brown Blue Male
## 6.42 Brown Blue Male
## 6.43 Brown Blue Male
## 6.44 Brown Blue Male
## 6.45 Brown Blue Male
## 6.46 Brown Blue Male
## 6.47 Brown Blue Male
## 6.48 Brown Blue Male
## 6.49 Brown Blue Male
## 7 Red Blue Male
## 7.1 Red Blue Male
## 7.2 Red Blue Male
## 7.3 Red Blue Male
## 7.4 Red Blue Male
## 7.5 Red Blue Male
## 7.6 Red Blue Male
## 7.7 Red Blue Male
## 7.8 Red Blue Male
## 7.9 Red Blue Male
## 8 Blond Blue Male
## 8.1 Blond Blue Male
## 8.2 Blond Blue Male
## 8.3 Blond Blue Male
## 8.4 Blond Blue Male
## 8.5 Blond Blue Male
## 8.6 Blond Blue Male
## 8.7 Blond Blue Male
## 8.8 Blond Blue Male
## 8.9 Blond Blue Male
## 8.10 Blond Blue Male
## 8.11 Blond Blue Male
## 8.12 Blond Blue Male
## 8.13 Blond Blue Male
## 8.14 Blond Blue Male
## 8.15 Blond Blue Male
## 8.16 Blond Blue Male
## 8.17 Blond Blue Male
## 8.18 Blond Blue Male
## 8.19 Blond Blue Male
## 8.20 Blond Blue Male
## 8.21 Blond Blue Male
## 8.22 Blond Blue Male
## 8.23 Blond Blue Male
## 8.24 Blond Blue Male
## 8.25 Blond Blue Male
## 8.26 Blond Blue Male
## 8.27 Blond Blue Male
## 8.28 Blond Blue Male
## 8.29 Blond Blue Male
## 9 Black Hazel Male
## 9.1 Black Hazel Male
## 9.2 Black Hazel Male
## 9.3 Black Hazel Male
## 9.4 Black Hazel Male
## 9.5 Black Hazel Male
## 9.6 Black Hazel Male
## 9.7 Black Hazel Male
## 9.8 Black Hazel Male
## 9.9 Black Hazel Male
## 10 Brown Hazel Male
## 10.1 Brown Hazel Male
## 10.2 Brown Hazel Male
## 10.3 Brown Hazel Male
## 10.4 Brown Hazel Male
## 10.5 Brown Hazel Male
## 10.6 Brown Hazel Male
## 10.7 Brown Hazel Male
## 10.8 Brown Hazel Male
## 10.9 Brown Hazel Male
## 10.10 Brown Hazel Male
## 10.11 Brown Hazel Male
## 10.12 Brown Hazel Male
## 10.13 Brown Hazel Male
## 10.14 Brown Hazel Male
## 10.15 Brown Hazel Male
## 10.16 Brown Hazel Male
## 10.17 Brown Hazel Male
## 10.18 Brown Hazel Male
## 10.19 Brown Hazel Male
## 10.20 Brown Hazel Male
## 10.21 Brown Hazel Male
## 10.22 Brown Hazel Male
## 10.23 Brown Hazel Male
## 10.24 Brown Hazel Male
## 11 Red Hazel Male
## 11.1 Red Hazel Male
## 11.2 Red Hazel Male
## 11.3 Red Hazel Male
## 11.4 Red Hazel Male
## 11.5 Red Hazel Male
## 11.6 Red Hazel Male
## 12 Blond Hazel Male
## 12.1 Blond Hazel Male
## 12.2 Blond Hazel Male
## 12.3 Blond Hazel Male
## 12.4 Blond Hazel Male
## 13 Black Green Male
## 13.1 Black Green Male
## 13.2 Black Green Male
## 14 Brown Green Male
## 14.1 Brown Green Male
## 14.2 Brown Green Male
## 14.3 Brown Green Male
## 14.4 Brown Green Male
## 14.5 Brown Green Male
## 14.6 Brown Green Male
## 14.7 Brown Green Male
## 14.8 Brown Green Male
## 14.9 Brown Green Male
## 14.10 Brown Green Male
## 14.11 Brown Green Male
## 14.12 Brown Green Male
## 14.13 Brown Green Male
## 14.14 Brown Green Male
## 15 Red Green Male
## 15.1 Red Green Male
## 15.2 Red Green Male
## 15.3 Red Green Male
## 15.4 Red Green Male
## 15.5 Red Green Male
## 15.6 Red Green Male
## 16 Blond Green Male
## 16.1 Blond Green Male
## 16.2 Blond Green Male
## 16.3 Blond Green Male
## 16.4 Blond Green Male
## 16.5 Blond Green Male
## 16.6 Blond Green Male
## 16.7 Blond Green Male
## 17 Black Brown Female
## 17.1 Black Brown Female
## 17.2 Black Brown Female
## 17.3 Black Brown Female
## 17.4 Black Brown Female
## 17.5 Black Brown Female
## 17.6 Black Brown Female
## 17.7 Black Brown Female
## 17.8 Black Brown Female
## 17.9 Black Brown Female
## 17.10 Black Brown Female
## 17.11 Black Brown Female
## 17.12 Black Brown Female
## 17.13 Black Brown Female
## 17.14 Black Brown Female
## 17.15 Black Brown Female
## 17.16 Black Brown Female
## 17.17 Black Brown Female
## 17.18 Black Brown Female
## 17.19 Black Brown Female
## 17.20 Black Brown Female
## 17.21 Black Brown Female
## 17.22 Black Brown Female
## 17.23 Black Brown Female
## 17.24 Black Brown Female
## 17.25 Black Brown Female
## 17.26 Black Brown Female
## 17.27 Black Brown Female
## 17.28 Black Brown Female
## 17.29 Black Brown Female
## 17.30 Black Brown Female
## 17.31 Black Brown Female
## 17.32 Black Brown Female
## 17.33 Black Brown Female
## 17.34 Black Brown Female
## 17.35 Black Brown Female
## 18 Brown Brown Female
## 18.1 Brown Brown Female
## 18.2 Brown Brown Female
## 18.3 Brown Brown Female
## 18.4 Brown Brown Female
## 18.5 Brown Brown Female
## 18.6 Brown Brown Female
## 18.7 Brown Brown Female
## 18.8 Brown Brown Female
## 18.9 Brown Brown Female
## 18.10 Brown Brown Female
## 18.11 Brown Brown Female
## 18.12 Brown Brown Female
## 18.13 Brown Brown Female
## 18.14 Brown Brown Female
## 18.15 Brown Brown Female
## 18.16 Brown Brown Female
## 18.17 Brown Brown Female
## 18.18 Brown Brown Female
## 18.19 Brown Brown Female
## 18.20 Brown Brown Female
## 18.21 Brown Brown Female
## 18.22 Brown Brown Female
## 18.23 Brown Brown Female
## 18.24 Brown Brown Female
## 18.25 Brown Brown Female
## 18.26 Brown Brown Female
## 18.27 Brown Brown Female
## 18.28 Brown Brown Female
## 18.29 Brown Brown Female
## 18.30 Brown Brown Female
## 18.31 Brown Brown Female
## 18.32 Brown Brown Female
## 18.33 Brown Brown Female
## 18.34 Brown Brown Female
## 18.35 Brown Brown Female
## 18.36 Brown Brown Female
## 18.37 Brown Brown Female
## 18.38 Brown Brown Female
## 18.39 Brown Brown Female
## 18.40 Brown Brown Female
## 18.41 Brown Brown Female
## 18.42 Brown Brown Female
## 18.43 Brown Brown Female
## 18.44 Brown Brown Female
## 18.45 Brown Brown Female
## 18.46 Brown Brown Female
## 18.47 Brown Brown Female
## 18.48 Brown Brown Female
## 18.49 Brown Brown Female
## 18.50 Brown Brown Female
## 18.51 Brown Brown Female
## 18.52 Brown Brown Female
## 18.53 Brown Brown Female
## 18.54 Brown Brown Female
## 18.55 Brown Brown Female
## 18.56 Brown Brown Female
## 18.57 Brown Brown Female
## 18.58 Brown Brown Female
## 18.59 Brown Brown Female
## 18.60 Brown Brown Female
## 18.61 Brown Brown Female
## 18.62 Brown Brown Female
## 18.63 Brown Brown Female
## 18.64 Brown Brown Female
## 18.65 Brown Brown Female
## 19 Red Brown Female
## 19.1 Red Brown Female
## 19.2 Red Brown Female
## 19.3 Red Brown Female
## 19.4 Red Brown Female
## 19.5 Red Brown Female
## 19.6 Red Brown Female
## 19.7 Red Brown Female
## 19.8 Red Brown Female
## 19.9 Red Brown Female
## 19.10 Red Brown Female
## 19.11 Red Brown Female
## 19.12 Red Brown Female
## 19.13 Red Brown Female
## 19.14 Red Brown Female
## 19.15 Red Brown Female
## 20 Blond Brown Female
## 20.1 Blond Brown Female
## 20.2 Blond Brown Female
## 20.3 Blond Brown Female
## 21 Black Blue Female
## 21.1 Black Blue Female
## 21.2 Black Blue Female
## 21.3 Black Blue Female
## 21.4 Black Blue Female
## 21.5 Black Blue Female
## 21.6 Black Blue Female
## 21.7 Black Blue Female
## 21.8 Black Blue Female
## 22 Brown Blue Female
## 22.1 Brown Blue Female
## 22.2 Brown Blue Female
## 22.3 Brown Blue Female
## 22.4 Brown Blue Female
## 22.5 Brown Blue Female
## 22.6 Brown Blue Female
## 22.7 Brown Blue Female
## 22.8 Brown Blue Female
## 22.9 Brown Blue Female
## 22.10 Brown Blue Female
## 22.11 Brown Blue Female
## 22.12 Brown Blue Female
## 22.13 Brown Blue Female
## 22.14 Brown Blue Female
## 22.15 Brown Blue Female
## 22.16 Brown Blue Female
## 22.17 Brown Blue Female
## 22.18 Brown Blue Female
## 22.19 Brown Blue Female
## 22.20 Brown Blue Female
## 22.21 Brown Blue Female
## 22.22 Brown Blue Female
## 22.23 Brown Blue Female
## 22.24 Brown Blue Female
## 22.25 Brown Blue Female
## 22.26 Brown Blue Female
## 22.27 Brown Blue Female
## 22.28 Brown Blue Female
## 22.29 Brown Blue Female
## 22.30 Brown Blue Female
## 22.31 Brown Blue Female
## 22.32 Brown Blue Female
## 22.33 Brown Blue Female
## 23 Red Blue Female
## 23.1 Red Blue Female
## 23.2 Red Blue Female
## 23.3 Red Blue Female
## 23.4 Red Blue Female
## 23.5 Red Blue Female
## 23.6 Red Blue Female
## 24 Blond Blue Female
## 24.1 Blond Blue Female
## 24.2 Blond Blue Female
## 24.3 Blond Blue Female
## 24.4 Blond Blue Female
## 24.5 Blond Blue Female
## 24.6 Blond Blue Female
## 24.7 Blond Blue Female
## 24.8 Blond Blue Female
## 24.9 Blond Blue Female
## 24.10 Blond Blue Female
## 24.11 Blond Blue Female
## 24.12 Blond Blue Female
## 24.13 Blond Blue Female
## 24.14 Blond Blue Female
## 24.15 Blond Blue Female
## 24.16 Blond Blue Female
## 24.17 Blond Blue Female
## 24.18 Blond Blue Female
## 24.19 Blond Blue Female
## 24.20 Blond Blue Female
## 24.21 Blond Blue Female
## 24.22 Blond Blue Female
## 24.23 Blond Blue Female
## 24.24 Blond Blue Female
## 24.25 Blond Blue Female
## 24.26 Blond Blue Female
## 24.27 Blond Blue Female
## 24.28 Blond Blue Female
## 24.29 Blond Blue Female
## 24.30 Blond Blue Female
## 24.31 Blond Blue Female
## 24.32 Blond Blue Female
## 24.33 Blond Blue Female
## 24.34 Blond Blue Female
## 24.35 Blond Blue Female
## 24.36 Blond Blue Female
## 24.37 Blond Blue Female
## 24.38 Blond Blue Female
## 24.39 Blond Blue Female
## 24.40 Blond Blue Female
## 24.41 Blond Blue Female
## 24.42 Blond Blue Female
## 24.43 Blond Blue Female
## 24.44 Blond Blue Female
## 24.45 Blond Blue Female
## 24.46 Blond Blue Female
## 24.47 Blond Blue Female
## 24.48 Blond Blue Female
## 24.49 Blond Blue Female
## 24.50 Blond Blue Female
## 24.51 Blond Blue Female
## 24.52 Blond Blue Female
## 24.53 Blond Blue Female
## 24.54 Blond Blue Female
## 24.55 Blond Blue Female
## 24.56 Blond Blue Female
## 24.57 Blond Blue Female
## 24.58 Blond Blue Female
## 24.59 Blond Blue Female
## 24.60 Blond Blue Female
## 24.61 Blond Blue Female
## 24.62 Blond Blue Female
## 24.63 Blond Blue Female
## 25 Black Hazel Female
## 25.1 Black Hazel Female
## 25.2 Black Hazel Female
## 25.3 Black Hazel Female
## 25.4 Black Hazel Female
## 26 Brown Hazel Female
## 26.1 Brown Hazel Female
## 26.2 Brown Hazel Female
## 26.3 Brown Hazel Female
## 26.4 Brown Hazel Female
## 26.5 Brown Hazel Female
## 26.6 Brown Hazel Female
## 26.7 Brown Hazel Female
## 26.8 Brown Hazel Female
## 26.9 Brown Hazel Female
## 26.10 Brown Hazel Female
## 26.11 Brown Hazel Female
## 26.12 Brown Hazel Female
## 26.13 Brown Hazel Female
## 26.14 Brown Hazel Female
## 26.15 Brown Hazel Female
## 26.16 Brown Hazel Female
## 26.17 Brown Hazel Female
## 26.18 Brown Hazel Female
## 26.19 Brown Hazel Female
## 26.20 Brown Hazel Female
## 26.21 Brown Hazel Female
## 26.22 Brown Hazel Female
## 26.23 Brown Hazel Female
## 26.24 Brown Hazel Female
## 26.25 Brown Hazel Female
## 26.26 Brown Hazel Female
## 26.27 Brown Hazel Female
## 26.28 Brown Hazel Female
## 27 Red Hazel Female
## 27.1 Red Hazel Female
## 27.2 Red Hazel Female
## 27.3 Red Hazel Female
## 27.4 Red Hazel Female
## 27.5 Red Hazel Female
## 27.6 Red Hazel Female
## 28 Blond Hazel Female
## 28.1 Blond Hazel Female
## 28.2 Blond Hazel Female
## 28.3 Blond Hazel Female
## 28.4 Blond Hazel Female
## 29 Black Green Female
## 29.1 Black Green Female
## 30 Brown Green Female
## 30.1 Brown Green Female
## 30.2 Brown Green Female
## 30.3 Brown Green Female
## 30.4 Brown Green Female
## 30.5 Brown Green Female
## 30.6 Brown Green Female
## 30.7 Brown Green Female
## 30.8 Brown Green Female
## 30.9 Brown Green Female
## 30.10 Brown Green Female
## 30.11 Brown Green Female
## 30.12 Brown Green Female
## 30.13 Brown Green Female
## 31 Red Green Female
## 31.1 Red Green Female
## 31.2 Red Green Female
## 31.3 Red Green Female
## 31.4 Red Green Female
## 31.5 Red Green Female
## 31.6 Red Green Female
## 32 Blond Green Female
## 32.1 Blond Green Female
## 32.2 Blond Green Female
## 32.3 Blond Green Female
## 32.4 Blond Green Female
## 32.5 Blond Green Female
## 32.6 Blond Green Female
## 32.7 Blond Green Female
Compute the chi-squared statistic with chisq.test( )
:
## List of 9
## $ statistic: Named num 107
## ..- attr(*, "names")= chr "X-squared"
## $ parameter: Named int 9
## ..- attr(*, "names")= chr "df"
## $ p.value : num 7.01e-19
## $ method : chr "Pearson's Chi-squared test"
## $ data.name: chr "he_tab"
## $ observed : 'table' int [1:4, 1:4] 36 66 16 4 9 34 7 64 5 29 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ hair: chr [1:4] "Black" "Brown" "Red" "Blond"
## .. ..$ eye : chr [1:4] "Brown" "Blue" "Hazel" "Green"
## $ expected : num [1:4, 1:4] 20.3 55.7 14.4 31.6 18.9 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ hair: chr [1:4] "Black" "Brown" "Red" "Blond"
## .. ..$ eye : chr [1:4] "Brown" "Blue" "Hazel" "Green"
## $ residuals: 'table' num [1:4, 1:4] 3.494 1.375 0.416 -4.907 -2.284 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ hair: chr [1:4] "Black" "Brown" "Red" "Blond"
## .. ..$ eye : chr [1:4] "Brown" "Blue" "Hazel" "Green"
## $ stdres : 'table' num [1:4, 1:4] 4.899 2.388 0.567 -7.296 -3.137 ...
## ..- attr(*, "dimnames")=List of 2
## .. ..$ hair: chr [1:4] "Black" "Brown" "Red" "Blond"
## .. ..$ eye : chr [1:4] "Brown" "Blue" "Hazel" "Green"
## - attr(*, "class")= chr "htest"
(What did we actually test?)
Use a permutation test to assess whether the relation between hair and eye color differs by sex.
To do this, we’ll:
Compute the sum of squared differences between each of the 16 proportions (4 eye x 4 hair colors). (test statistic)
Compute the same thing, after shuffling up the sex
column, a bunch of times.
Compare the observed value to the distribution under permutations from (2).