This part contains a lot of interesting lists, and it's a good place for you to start using the book. Here are some suggestions for using the lists to explore career options:
- The table of contents at the beginning of this book presents a complete listing of the list titles in this section. You can browse the lists or use the table of contents to find those that interest you most.
- We gave the lists clear titles, so most require little explanation. We provide comments for each group of lists.
- As you review the lists, one or more of the jobs may appeal to you enough that you want to seek additional information. As this happens, mark that job (or, if someone else will be using this book, write it on a separate sheet of paper) so that you can look up the description of the job in Part II.
- All data used to create these lists comes from the U.S. Department of Labor and the Census Bureau. The earnings figures are based on the average annual pay received by full-time workers. Some occupations have high percentages of part-time workers, and those workers would receive, of course, proportionately less pay on a weekly or annual basis. Because the earnings represent the national averages, actual pay rates can vary greatly by location, amount of previous work experience, and other factors.
Some Details on the Lists
The sources of the information we used in constructing these lists are presented in this book's introduction. Here are some additional details on how we created the lists:
- We excluded some jobs for which very little information is available. In the full list of 1,167 jobs that are described in release 9 of the U.S. Department of Labor's O*NET database, 212 have no information beyond a definition and, in some cases, a list of tasks. These are either catch-all titles (such as "Financial Specialists, All Other") that make the O*NET as comprehensive as possible or dummy occupations that help the O*NET match up better with occupational information from other government agencies. Census Bureau data is available for some of them, but no O*NET data is available for them, so we dropped them from consideration. We also reluctantly excluded seven jobs because no wage information is available for them: Actors; Biologists; Dancers; Human Resources Managers; Hunters and Trappers; Musicians, Instrumental; and Singers.
- We excluded some jobs that are shrinking or that offer very few opportunities. Among the 948 jobs for which we have both O*NET and wage information, 13 are expected to employ fewer than 500 workers per year and to shrink rather than grow in workforce size: Camera and Photographic Equipment Repairers; Fabric Menders, Except Garment; Fire Inspectors; Fire Investigators; Forest Fire Inspectors and Prevention Specialists; Loading Machine Operators, Underground Mining; Mathematicians; Mine Cutting and Channeling Machine Operators; Mining and Geological Engineers, Including Mining Safety Engineers; Radio Operators; Refractory Materials Repairers, Except Brickmasons; Shoe Machine Operators and Tenders; and Shuttle Car Operators. These jobs can't be considered "best jobs," so we excluded them from consideration for this book.
- We collapsed a number of specialized postsecondary education jobs into one title. The government database we used for the job titles and descriptions included 36 job titles for postsecondary educators, yet the data source we used for growth and number of openings provided data only for the more general job of Teachers, Postsecondary. To make our lists more useful, we included only one listing-Teachers, Postsecondary- rather than separate listings for each specialized postsecondary education job. We did, however, include descriptions for all the specific postsecondary teaching jobs in Part II (except two for which no detailed information is available). Should you wonder, here are the more-specialized titles: Agricultural Sciences Teachers, Postsecondary; Anthropology and Archeology Teachers, Postsecondary; Architecture Teachers, Postsecondary; Area, Ethnic, and Cultural Studies Teachers, Postsecondary; Art, Drama, and Music Teachers, Postsecondary; Atmospheric, Earth, Marine, and Space Sciences Teachers, Postsecondary; Biological Science Teachers, Postsecondary; Business Teachers, Postsecondary; Chemistry Teachers, Postsecondary; Communications Teachers, Postsecondary; Computer Science Teachers, Postsecondary; Criminal Justice and Law Enforcement Teachers, Postsecondary; Economics Teachers, Postsecondary; Education Teachers, Postsecondary; Engineering Teachers, Postsecondary; English Language and Literature Teachers, Postsecondary; Environmental Science Teachers, Postsecondary; Foreign Language and Literature Teachers, Postsecondary; Forestry and Conservation Science Teachers, Postsecondary; Geography Teachers, Postsecondary; Graduate Teaching Assistants; Health Specialties Teachers, Postsecondary; History Teachers, Postsecondary; Home Economics Teachers, Postsecondary; Law Teachers, Postsecondary; Library Science Teachers, Postsecondary; Mathematical Science Teachers, Postsecondary; Nursing Instructors and Teachers, Postsecondary; Philosophy and Religion Teachers, Postsecondary; Physics Teachers, Postsecondary; Political Science Teachers, Postsecondary; Psychology Teachers, Postsecondary; Recreation and Fitness Studies Teachers, Postsecondary; Social Work Teachers, Postsecondary; Sociology Teachers, Postsecondary; Vocational Education Teachers, Postsecondary.
- Some jobs have the same scores for one or more data elements. For example, in the list of occupations ordered by rate of job growth, two occupations (Astronomers and Construction Managers) are growing at the same rate, 10.4%. Therefore we ordered these two jobs alphabetically, and their order has no other significance. There was no way to avoid these ties, so simply understand that the difference of several positions on a list may not mean as much as it seems.
- Some jobs share certain data elements. In some cases, our data sources do not provide separate information for several separate jobs but instead provide it for an umbrella occupation. In these cases we have to print the same information for two, three, or more jobs. That can be misleading if you don't understand that these jobs share data. The section on "Data Complexities" in the introduction explains the full implications of this data-sharing. For here, we'll say simply that when occupations share data, the figures for earnings and job growth represent the averages for the occupations, and the figure for job openings represents the total number of job openings for the occupations. To remind you about how to read these figures, we print footnotes below lists to identify all the jobs that share job-openings data.
We hope you find these lists both interesting and helpful. They can help you explore your career options in a variety of interesting ways. We suggest you find the ones that are most helpful to you and focus your attention on them. Enjoy!