This dataset contains some variables regarding household expenses for a sample of 105 households selected from a list of landline phones (let say, frame A) in a particular city in a specific month.
Usage
DatA
Arguments
Format
Domain
A string indicating the domain each household belongs to. Possible values are "a" if household belongs to domain a or "ab" 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.
Stratum
A numeric value indicating the stratum each household belongs to.
Details
The sample, of size $n_A = 105$, has been drawn from a population of $N_A = 1735$ households with landline phone according to a stratified random sampling. Population units were divided in 6 different strata.
Population sizes of these strata are $N_A^h = (727, 375, 113, 186, 115, 219)$. $N_{ab} = 601$ of the households composing the population have, also, mobile phone. On the other hand, frame totals for auxiliary variables in this frame are $X_{Income}^A = 4300260$ and $X_{Taxes}^A = 215577$.
data(DatA)
attach(DatA)
#Let perform a brief descriptive analysis for the three main variablesparam <- data.frame(Feed, Clo, Lei)
summary (param)
hist (Feed)
hist (Clo)
hist (Lei)