The weakness of the survey is that these are median earnings that have been listed and not the individual de facto earnings of the people under their respective occupation which cannot clearly state whether the occupation is really a high paying one for the individual. Therefore the conclusion could be erroneous under the data obtained.

Data on earnings by type of industry and class of worker are limited to full-time, year-round civilian workers 16 years or older. Industry refers to the kind of business conducted by a person’s employing organization. The industries for which data are collected in the ACS are commonly grouped into sectors. Table 7 shows the 20 major industry sectors. Men earned the most in the 2007 ACS in two of those sectors: the management of companies and enterprises sector ($76,630) and the professional, scientific, and technical services sector ($75,320). Men in the accommodation and food services sector had the lowest median earnings ($25,611). For women, several sectors had relatively high median earnings in the 2007 ACS. In the following sectors, women’s median earnings were $45,000 or higher management of companies and enterprises ($47,715); professional, scientific, and technical services ($47,292); mining ($47,146); and utilities ($45,539).  As with men, the sector with the lowest earnings for women was accommodation and food services ($20,708). In each of the 20 industry sectors, men earned more than women.

Analysis of Data

Population: A collection, or set, of individuals, objects, or events whose properties are to be analyzed. The population is the complete collection of individuals or objects that are of interest to the sample collector. The population of concern must be carefully defined and is considered fully defined only when its membership list of elements is specified. The set of “all students who have ever attended a U.S. college” is an example of a well-defined population. Typically, we think of a population as a collection of people. However,   the population could be a collection of animals, manufactured objects, whatever. For example, here the entire population of United States is the population that we are considering in the sample survey.

Sample: A subset of a population. A sample consists of the individuals, objects, or measurements selected from the population by the sample collector.   

Parameter:  A numerical value summarizing all the data of an entire population. The “average” age at the time of admission for all students who have ever attended our college and the “proportion” of students who were older than 21 years of age, when they entered college are examples of two population parameters. A parameter is a value that describes the entire population.  For example the true parameters here are the income in dollars of both men and women in their respective occupations.

The central limit theorem states that even if a population distribution is strongly non-normal, its sampling distribution of means will be approximately normal for large sample sizes (over 30). The central limit theorem makes it possible to use probabilities associated with the normal curve to answer questions about the means of sufficiently large samples.

Therefore here it is assumed that the sample consists of equal number of people over all occupations but the central limit theorem will help to extrapolate the results to the complete population even if the sample is not normal.

The data is assumed to be from a sample which is normally distributed therefore as the sample is large enough we can apply the results to the entire population of United States.

Conclusion:

The survey is very important from the business perspective as men and women from all across United States will be able to realize a high income by choosing the correct profession.

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