BigCity: Full Person-level Population Database

In TeachingSampling: Selection of Samples and Parameter Estimation in Finite Population

Description

This data set corresponds to some socioeconomic variables from 150266 people of a city in a particular year.

Usage

data(BigCity)

Format

HHID

The identifier of the household. It corresponds to an alphanumeric sequence (four letters and five digits).

PersonID

The identifier of the person within the household. NOTE it is not a unique identifier of a person for the whole population. It corresponds to an alphanumeric sequence (five letters and two digits).

Stratum

Households are located in geographic strata. There are 119 strata across the city.

PSU

Households are clustered in cartographic segments defined as primary sampling units (PSU). There are 1664 PSU and they are nested within strata.

Zone

Segments clustered within strata can be located within urban or rural areas along the city.

Sex

Sex of the person.

Income

Per capita monthly income.

Expenditure

Per capita monthly expenditure.

Employment

A person's employment status.

Poverty

This variable indicates whether the person is poor or not. It depends on income.

Author(s)

Hugo Andres Gutierrez Rojas [e-mail]

References

Gutierrez, H. A. (2009), Estrategias de muestreo: Diseno de encuestas y estimacion de parametros. Editorial Universidad Santo Tomas.

See Also

Lucy, BigLucy

Examples

data(BigCity)
attach(BigCity)

estima <- data.frame(Income, Expenditure)
# The population totals
colSums(estima)
# Some parameters of interest
table(Poverty, Zone)
xtabs(Income ~ Poverty + Zone)
# Correlations among characteristics of interest
cor(estima)
# Some useful histograms
hist(Income)
hist(Expenditure)
# Some useful plots
boxplot(Income ~ Poverty)
barplot(table(Employment))
pie(table(MaritalST))

Example output

Loading required package: dplyr

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

Loading required package: magrittr
     Income Expenditure 
   87893117    56452461 
          Zone
Poverty    Rural Urban
  NotPoor  45380 50764
  Extreme   6944  5804
  Relative 19778 21596
          Zone
Poverty         Rural      Urban
  NotPoor  26199645.9 46224046.7
  Extreme    888436.8  1158988.2
  Relative  5071369.9  8350629.3
               Income Expenditure
Income      1.0000000   0.5989276
Expenditure 0.5989276   1.0000000

TeachingSampling documentation built on April 22, 2020, 1:05 a.m.