Generate a random vector of genders.
sex(
n,
x = c("Male", "Female"),
prob = c(0.51219512195122, 0.48780487804878),
name = "Sex"
)gender(
n,
x = c("Male", "Female"),
prob = c(0.51219512195122, 0.48780487804878),
name = "Gender"
)
The number elements to generate. This can be globally set within
the environment of r_data_frame
or r_list
.
A vector of length 2 to sample from.
A vector of probabilities to chose from.
The name to assign to the output vector's varname
attribute. This is used to auto assign names to the column/vector name when
used inside of r_data_frame
or r_list
.
Returns a random factor vector of gender elements.
The genders and probabilities used match approximate gender make-up:
Gender | Percent |
Male | 51.22 % |
Female | 48.78 % |
Other variable functions:
age()
,
animal()
,
answer()
,
area()
,
car()
,
children()
,
coin()
,
color
,
date_stamp()
,
death()
,
dice()
,
dna()
,
dob()
,
dummy()
,
education()
,
employment()
,
eye()
,
grade_level()
,
grade()
,
group()
,
hair()
,
height()
,
income()
,
internet_browser()
,
iq()
,
language
,
level()
,
likert()
,
lorem_ipsum()
,
marital()
,
military()
,
month()
,
name
,
normal()
,
political()
,
race()
,
religion()
,
sat()
,
sentence()
,
sex_inclusive()
,
smokes()
,
speed()
,
state()
,
string()
,
upper()
,
valid()
,
year()
,
zip_code()
# NOT RUN {
sex(10)
100*table(sex(n <- 10000))/n
# }
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