Description

About 800 students studying undergraduate statistics were asked many lifestyle questions.

Usage

Format

A data frame with 804 observations on the following 29 variables.

sex

Gender, a factor, (female or male)

age

age in years, a numeric vector

eyes

eye colour, a factor, (blue, brown, green, hazel or other)

piercings

Number of body piercings, a numeric vector

pierced

Any body piercings? a factor, (Yes or No)

tattoos

Number of tattoos, a numeric vector

tattooed

Any tattoos? a factor, (Yes or No)

glasses

Wears glasses etc.? a factor, (Yes or No)

sleep

Average number of hours of sleep per night, a numeric vector

study

Average number of hours of study per week, a numeric vector

tv

Average number of hours watching TV per week, a numeric vector

movies

Number of movies seen at a cinema during the last 3 months, a numeric vector

movies3m

Seen movies in last 3 months? a factor, (Yes or No)

sport

Favourite sport, a factor, about 19 of them

entertainment

Favourite entertainment, a factor, about 15 of them

fruit

Favourite fruit a factor, about 13 of them

income

Average income during semester per week, a numeric vector

rent

Amount spent on rent or room and board per week, a numeric vector

clothes

Average amount spent on clothes per month, a numeric vector

hair

Average cost to get a hair-cut, a numeric vector

tobacco

Average amount spent on tobacco per week, a numeric vector

smokes

Smokes? a factor, (Yes or No)

alcohol

Average amount spent on alcohol per week, a numeric vector

buy.alcohol

Buys (purchases) alcohol? a factor, (Yes or No)

sendtxt

Average number text messages sent per day, a numeric vector.

receivetxt

Average number text messages received per day, a numeric vector.

txts

Uses text messaging? a factor, (Yes or No)

country

Country of birth, a factor, about 54 of them

status

Student status, a factor, (International, NZ.Citizen, NZ.Resident)

Details

This data was collected online and anonymously in 2010. The respondents were students studying an undergraduate statistics course at a New Zealand university. Possibly there are duplicate students (due to failing and re-enrolling). All monies are in NZD. Note the data has had minimal checking. Most numerical variables tend to have measurement error, and all of them happen to be all integer-valued.

Examples