DatB {Frames2}

Database of household expenses for frame B

Description

This dataset contains some variables regarding household expenses for a sample of 135 households selected from a list of mobile phones (let say, frame B) in a particular city in a specific month.

Usage

DatB

Format

Domain

A string indicating the domain each household belongs to. Possible values are "b" if household belongs to domain b or "ba" if household belongs to overlap domain.

Feed

Feeding expenses (in euros) at the househould

Clo

Clothing expenses (in euros) at the household

Lei

Leisure expenses (in euros) at the household

Inc

Household income (in euros). Values for this variable are only available for households included in frame A. For households included in domain b, value of this variable is set to 0.

Tax

Household municipal taxes (in euros) paid. Values for this variable are only available for households included in frame A. For households included in domain b, value of this variable is set to 0.

M2

Square meters of the house. Values for this variable are only available for households included in frame B. For households included in domain a, value of this variable is set to 0.

Size

Household size. Values for this variable are only available for households included in frame B. For households included in domain a, value of this variable is set to 0.

ProbA

First order inclusion probability in frame A. This probability is 0 for households included in domain b.

ProbB

First order inclusion probability in frame B. This probability is 0 for households included in domain a.

Details

The sample, of size n_B = 135, has been drawn from a population of N_B = 1191 households with mobile phone according to a simple random sampling without replacement design. N_{ab} = 601 of these households have, also, landline phone. On the other hand, frame totals for auxiliary variables in this frame are X_{Metres2}^B = 176553 and X_{Size}^B = 3529

See Also

PiklB

Examples

data(DatB)
attach(DatB)
#Let perform a brief descriptive analysis for the three main variables
param <- data.frame(Feed, Clo, Lei)
summary (param)
hist (Feed)
hist (Clo)
hist (Lei)