BigLucy: Full Business Population Database

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

Description

This data set corresponds to some financial variables of 85396 industrial companies of a city in a particular fiscal year.

Usage

data(BigLucy)

Format

ID

The identifier of the company. It correspond to an alphanumeric sequence (two letters and three digits)

Ubication

The address of the principal office of the company in the city

Level

The industrial companies are discrimitnated according to the Taxes declared. There are small, medium and big companies

Zone

The country is divided by counties. A company belongs to a particular zone according to its cartographic location.

Income

The total ammount of a company's earnings (or profit) in the previuos fiscal year. It is calculated by taking revenues and adjusting for the cost of doing business

Employees

The total number of persons working for the company in the previuos fiscal year

Taxes

The total ammount of a company's income Tax

SPAM

Indicates if the company uses the Internet and WEBmail options in order to make self-propaganda.

ISO

Indicates if the company is certified by the International Organization for Standardization.

Years

The age of the company.

Segments

Cartographic segments by county. A segment comprises in average 10 companies located close to each other.

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, BigCity

Examples

data(BigLucy)
attach(BigLucy)
# The variables of interest are: Income, Employees and Taxes
# This information is stored in a data frame called estima
estima <- data.frame(Income, Employees, Taxes)
# The population totals
colSums(estima)
# Some parameters of interest
table(SPAM,Level)
xtabs(Income ~ Level+SPAM)
# Correlations among characteristics of interest
cor(estima)
# Some useful histograms
hist(Income)
hist(Taxes)
hist(Employees)
# Some useful plots
boxplot(Income ~ Level)
barplot(table(Level))
pie(table(SPAM))

Example output

   Income Employees     Taxes 
 36634733   5391992   1008426 
     Level
SPAM    Big Medium Small
  no    910  10185 22260
  yes  1995  15610 34336
        SPAM
Level          no      yes
  Big     1116990  2512720
  Medium  6679820 10377465
  Small   6288497  9659241
             Income Employees     Taxes
Income    1.0000000 0.6433037 0.9166732
Employees 0.6433037 1.0000000 0.6448609
Taxes     0.9166732 0.6448609 1.0000000

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