Demographics is the mathematical study of populations, and groups within populations.
Demographics uses characteristics of a population to develop policies to serve the people, to guide the development and marketing of products that will be popular, to conduct surveys that reveal opinions and how these opinions vary among various sectors of those surveyed, and of continuing news interest, to analyze polls and results related to elections.
Math lies at the heart of demographics, in the methods used to assemble information that is accurate and representative of the population. Without the accuracy and precision that mathematics brings to the enterprise, the demographic analysis will not provide meaningful information.
But demographics is not entirely concerned with math. Because demographics is also concerned with factors like cultural characteristics and social views, factors such as how people think about the issue at hand are also measured. Or, even less precisely, demographics can be concerned with how people 'feel' about something. These sorts of factors are more difficult to put into numbers and they are described as being qualitative (measuring quality) as opposed to quantitative (measuring an amount). Qualitative and quantitative aspects are often combined to form a 'demographic profile.'
Some of the mathematical operations that can be useful in the analysis of demographic information include the mean (the average of a set of numbers that is determined by adding some aspect of those numbers and dividing by some aspect of the numbers), the median (the value that is in the middle of a range of values) and the distribution (the real or theoretical chances of occurrence of a set of values, usually patterned with the most frequently-occurring values in the middle with less frequently-occurring values tailing off in either direction.)
Demographic information can be very powerful. It can reveal previously unrecognized aspects of a population and can be used to predict future trends. Part of the reliability of the demographic information comes from the mathematical operations used to derive the data.
The analysis of the 2004 general election (also called the Presidential election) in the United States offers an example of the use of demographics to analyze the voting patterns. By asking people questions about their beliefs and opinions on a variety of issues, and by utilizing databases
that yield information on aspects such as age, gender, and income (more on this sort of information is presented below), a more complete picture can be built of the characteristics of those who voted for a certain candidate.
For example, exit polls (asking people questions after they have voted) were used to determine voter preferences and what issues were important in deciding how to cast votes in various races.
These characteristics can be considered along with information on employment, geographic residence, homeowner status, and other factors, to build up a profile of a 'typical' person who will vote for a particular politician.
These demographic patterns were known beforehand to campaign organizers, who conducted their own surveys of the public. So, aware of the characteristics of a certain segment of the population and the percentage of total voters who fit this demographic, candidates target specific groups with specific messages and promises.
Many countries periodically undergo a process known as a census. Essentially, a census is an organized gathering of information about the adult population of the country. Citizens and other eligible residents of the country complete a form or participate in an interview. Many questions are asked in a census. Example categories include age, gender, employment status, income range, educational background, marital status, number of dependents, ethnic background, place of residence (both geographically and in terms of whether a residence is owned or rented), history of residence change, and record of military service.
These categories of information can be analyzed to provide details of the characteristics of the population, and the proportions of the populations that make up each of the characteristic groups.
The demographic information in a census is used by governments to develop policies that will hopefully best
|Cohort||Dates of birth||Events||Example characteristics|
|Great Depression||1912–1921||Depression, high unemployment, hard times||Need for financial security and comfort, Conservative|
|World War II||1922–1927||War, women working, a common enemy||The common good, patriotism, teamwork|
|Generation X||1965–1976||Space disasters, AIDS, safe sex, Berlin wall||Need for emotional security and independence, importance of money|
|Generation N||1977–present||September 11, Iraq wars, Internet||Need for physical safety, patriotism, increased fear, comfortable with change|
serve their constituents. As well, the information represents a wonderful database for marketers to sell their wares. For example, it would not make sense for car company to target a region of high unemployment as a market for its top-of-the-line luxury car.
Demographics and the Marketplace
Demographics such as contained in a census have long been a tool of those who make and sell products. Knowing the characteristics, likes and dislikes of the buying public is obviously important when trying to sell a product.
The baby boom that occurred during the 1950s and 1960s provides a prime example of an identified demographic group. The increased birth rate in North America during those decades will have a number of effects that have and will continue to ripple through the ensuing decades. In the first few years, there was an increased demand for products to do with infants (baby food, diapers). Savvy entrepreneurs took advantage of the knowledge that an increasing number of new parents identified strongly with environmental protection to market organic baby foods and re-popularize nondisposable diapers. In the following few years as infants became youngsters, adolescents and young adults there was a succession of increased demands for children's toys and clothes, better educational facilities, housing and furniture. In the last decade, as the baby boomers have reached middle age, there has been an increased demand for certain types of vehicles such as SUVs, for health clubs and weight loss centers to help trim sagging waistlines, and for expertise in investment help as retirement draws closer. In the coming decades, as the baby boomers become infirmed, there will be a demand for more health-care services and funeral services.
Baby boomers came into the world at about the same time and, as they age, experience similar things and have similar demands. This generation is a perfect example of what was termed, way back in the 1920s, a 'generational cohort.' The designation has roots in mathematics. In statistical analysis, it can be advantageous and more meaningful to group items in cohorts that are similar in whatever aspect(s) is being studied. Historic examples of other demographic cohorts, and their associated characteristics, are given in Table 1.
GEOGRAPHIC INFORMATION SYSTEM TECHNOLOGY
Geographic information system (GIS) technology is the use of computers and computer databases to assemble information that have a geographical component. The information can come from reports, topographical maps that display elevation, land use maps, photographs, and satellite images of an area.
Knowledge of the geography can be combined with other data including information on age, gender, employment, health, and other aspects that are collected in a census, and data collected from other surveys. The aim is to provide a more complete picture of a region, in which demographic characteristics can be related to geographical features.
As an example, combining GIS data with population information could reveal that there is a higher incidence of fatal diseases in rural and mountainous areas. This could help health care providers in designing better ambulance service or telephone-based health advice.
The analysis and interpretation of geographic information can be a mathematical process. Equations can be applied to images to help sort out background detail from the more relevant information. Data can be statistically analyzed to reveal important associations between various data groups.
Where to Learn More
Foote, D.K., and D. Stoffman. Boom Bust & Echo: Profiting from the Demographic Shift in the 21st Century. Toronto: Stoddart, 2000.
Rowland, D.T. Demographic Methods and Concepts. New York: Oxford University Press, 2003.
Wallace, P. Agequake: Riding the Demographic Rollercoaster Shaking Business, Finance, and Our World. London: Nicholas Brealey Publishing, 2001.
Gale Document Number: GALE|CX3447900026