In the comment stream from recent posts, I've had a couple of people take me to task for making sweeping generalities, and for trying to create broad brush generations that act to unify peoples actions. I'd like to focus on both of these topics here.
In statistics, you have three core concepts that together describe what I'd call the "middle values". One of these is the average - you take a number of samples from a set to determine a given property sum, then you divide it by the number of samples. Averages can actually determine the behavior of a population reasonably well when that population is large enough - relative small outliers tend to get smoothed out. However, for smaller populations (under 800 or so people, it turns out) significant outliers can skew the data significantly. This is why in general why talking about the average (or mean) value, you usually want to give two values - the mean μ and the standard deviation σ. For Gaussian distribution curves, this is a pretty good measure of how widely dispersed the data is around that mean value, and hence the likelihood that the mean provides a representative value for the property being measured.
The median value indicates the value that, for a population is such that there as many (give or take one) values above that median as there are below it. The value of the median is that it provides a measure of whether the data set is skewed in one or another direction, and hence is not symmetrical. The closer the median is to the mean, the more likely that the distribution is bell shaped, whereas the farther it is, the greater the likelihood that the distribution either has several significant outliers or that there may in fact be more than one distribution peak involved (which in turn usually indicates that the variables involved are in fact hiding two or more distinct properties that each factor into a standard gaussian around different means).
With this elementary bit of statistics aside, I want to focus on two other terms - generalities and stereotypes. A generality is an assumption that for any given property or characteristic, by knowing the value(s) of a subset of a group one can generalize this up to the group as a whole. Most surveys that are done utilize this principle, and so long as you have a Gaussian distribution (not necessarily a given) and a sufficiently large sample (800+ or so), you can ascertain the degree of confidence in making such generalities.
Stereotypes, on the other hand, involve going from applying generalizations to individuals within a given sample. Having determined a generalization, as you then apply it to smaller and smaller groups, you also have to take into account that the probability that a given person within that sample has a given characteristic drops according to a clearly defined relationships with the standard deviation. The lower the standard deviation, the higher the chance an individual in that group has that property, the higher the standard deviation, the lower that chance.
When talking of generations, what you are in fact usually describing is a cohort that has a number of mutually common characteristics above the mean expected value for all individuals. These characteristics usually come about because of shared common experiences, and are usually consequently driven by demographics. As an example of this, consider the US space program and its effects on pedagogy. In 1958, Sputnik was launched. The US space program really started in about 1961, but from the standpoint of public awareness, John Glenn's historical flight in the Mercury program in 1962 was in many respects the start. From 1962 to 1974, then, the space program became a seminal part of public education, with the high point being the landing on the Moon in 1969. By 1974, the impact of the moon missions had dropped as other factors, including the outcry over the Vietnam War and the scandals of Watergate, as well as just general fatigue, made the moon missions less and less effective from about 1971 onward.
From the standpoint of grade school and high school kids, this had a huge impact, probably more than it did for any other group, in great part because the school curricula was built around those programs. This group (for people born from about 1955 to 1972 or so) had a higher proportion per capita of engineers, scientists and researchers graduate from college than at any time before or since. By 1977, when the youngest of this group was entering into grade school, this big STEM push was fading, in part because a conservative agenda was reasserting itself in the school system and there were fewer "gee-whiz" engineering innovations happening to drive the push.
Significantly, 1962 marked another significant point. The number of babies born had risen steadily from about 1943 onward as economic conditions improved and soldiers returned from World War II with significant disposable income saved up. This peaked in 1955, and then started to drop as the war generation reached forty and menopause began to set in. It also dropped more precipitously because of the advent of the first birth control pill in 1960, to the extent that by 1973 there were only 75% as many childrern born as at the peak.
Most demographers tend to measure populations from the zero-point between a peak or trough (or when the population Gaussian reaches a certain number of standard deviations from the peak.) However, sociologically, a better measure of a population cohort may be that population at either a peak or a trough + five years. In general, those born before a peak will have more of societies resources available to them - attention, money, policy, etc. - while those after the peak will see those aspects diminish. The five years has to do with the fact that until Kindergarten, the impact of the larger world on a child is fairly minimal - babies and toddlers will behave the same regardless of when they are born and the way that we treat them will tend to be the same as well.
However, by age five, the children are entering into universal education, which means that for the next ten to sixteen years, there is a homogenization effect - all kids will tend to experience the same culture present at any given time, and will correspondingly be shaped by that culture. They will watch the same shows, hear the same issues being discussed (albeit from potentially different viewpoints) at the dinner table, will wear roughly the same fashions and will be affected by the same educational indoctrination). This has a huge impact upon future development of people, because during their formative years they have a common cultural reservoir from which to draw.
Now, obviously, no one is going to grow up to be a clone of everyone else. Gender, regional differences, growing up in urban vs. rural vs. suburban households, ethnicity, family history and personal temperament will all play a significant role as well. However, if you take the population as an aggregate at any point in time and look at the population of a given age at that time, generational deviance from the norm for specific characteristics will be well above the long term aggregate for that age, and those deviations are more pronounced for distinct cohorts of ages.
Births per capita troughed in 1973, and peaked in 1990, but bucked the pattern of previous generations by troughing in 2002 at very nearly the peak value and then rising again until 2008, at which point the birth population began to drop precipitously through to this year. This indicates that birth rates are not purely cyclical, but are affected by societal changes (long term declines in earning power meant ered) were marrying later, and consequently having both fewer kids and skewing the curves from previous generations) and by economic ones (the birth rate was trending upward in 2007 then dropped sharply by 2008 as the global economy sputtered). With the advent of oral contraceptives fifty years ago, the ability of women to choose when they get pregnant is significantly enhanced, and this no doubt will continue to alter what had been fairly distinct generational patterns before (BPC was nowhere near as sensitive to economic conditions before the Pill).
My goal with these essays is not to create stereotypes, but rather, from a sea of data, whether there are consistent patterns that emerge about the evolution of society. I see the Millennials - those born between 1980 and 2000 as in general being very connected and artistically inclined, because this was the first cohort to have digitalized media and the tools to use them from the time they were in kindergarten. This will make them very different from those born prior to 1980, who largely wrote the tools. However, this does not mean that a person picked at random from this group will be permanently connected to their iPads and music players - only that statistically it is more likely that they will. In effect, this is an attempt to identify and model the various cohorts, in order to better understand how society will change as they enter different phases of their life as a group.