This data set corresponds to a random sample of BigLucy. It contains some financial variables of 2396 industrial companies of a city in a particular fiscal year.
The identifier of the company. It correspond to an alphanumeric sequence (two letters and three digits)
The address of the principal office of the company in the city
The industrial companies are discrimitnated according to the Taxes declared. There are small, medium and big companies
The city is divided by geoghrafical zones. A company is classified in a particular zone according to its address
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
The total number of persons working for the company in the previuos fiscal year
The total ammount of a company's income Tax
Indicates if the company uses the Internet and WEBmail options in order to make self-propaganda.
Hugo Andres Gutierrez Rojas email@example.com
Gutierrez, H. A. (2009), Estrategias de muestreo: Diseno de encuestas y estimacion de parametros. Editorial Universidad Santo Tomas.
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data(Lucy) attach(Lucy) # 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))
Income Employees Taxes 1035217.0 151950.0 28653.5 Level SPAM Big Medium Small no 26 291 620 yes 57 446 956 SPAM Level no yes Big 31914 71792 Medium 190852 296499 Small 175186 268974 Income Employees Taxes Income 1.0000000 0.645536 0.9169541 Employees 0.6455360 1.000000 0.6468550 Taxes 0.9169541 0.646855 1.0000000
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