1. Conventional wisdom is a body of assertions and beliefs that is generally
recognized as part of a culture’s common knowledge (i.e., numbers don’t lie is a
piece of our conventional wisdom so we place a lot of importance on statistics).
Sociology is the scientific study of human group behavior (looks at how groups,
networks, institutions and social conditions shape the way people act and see the
sociology requires evidence while common sense can be based on belief,
faith, logicabsent evidence
sociology is based on systematic organized evidence rather than single
anecdote (what applies to one person may not apply to all groups of
sociology differs from psychology in that psychology looks at forces internal to
individuals and how they affect behavior while sociology looks at forces external
to individual and how they affect behavior. Rather than individual personality,
brain wiring, personality factors sociology looks at influence of broader social
patterns, forces and networks
Durkheim’s study of suicide shows us how the two are different when it comes to
preventing an individual’s wish for suicide:
•psych= will help by looking at the person’s internal or biological issues
•soc= will explain why some groups are more likely to commit suicide than
others. Consult a sociologist for how to lower suicide rates but a psychologist for
how to help and individual.
anomic suicide: suicide from lack of regulation (too much freedom creates a
situation some are unable to handle). Kid that goes off to college and can’t handle
the freedom/forming their own identity, or kid neglected by parents.
altruistic suicide: suicide from too much integration (one is so connected and
committed to community that they have no sense of self/individual). Suicide
egoistic suicide: suicide from lack of social integration: someone who is lonely,
has few friends, feels alone. Teen bullied/friendless at school.
Bad statistics come from:
•deceptive definitions/misleading measures
•mangled, transformed or mutant specifics
•nonrepresentative samples/convenience samples
•faulty or spurious causation
Good statistics are:
•based on more than just a guess
•clear, reasonable measures
•not mangled or transformed
•random, representative samples
•controls for other variables and explanations 5. Mutant stats= not that the number itself is wrong, but that its been mutated to represent
something its not, like in a game of telephone. An example is the study about how many
women have anorexia in America (lets say 50,000). The statistic became mutant so that it
was presented as the amount of women dying from anorexia each year, which isn’t what
6. Good samples are representative of the population you’re trying to study.
Representative samples make sure to represent the entire population as best you can (not
just people you know, people in all facets of the population). Convenience samples are
probably not representative and involve you sampling easy choices like people you know,
people that live by you and those easiest to reach.
7. Faulty causation: the statistics may look like they causally support something, but this
may not (it might just be correlation instead). You have to be careful to not use single
dimensional explanations for multidimensional problems (taking one case and applying
to all examples and situations). For example, if a statistician was to say 58% of people get
more happy in the spring, so spring causes happiness. There’s a definite correlation
between happiness and spring, but it may not be spring itself that causes it.
8. Chambliss’ main point is that excellence is less the result of skill than it is of perfecting
the small, minute, mundane parts of a skill/task in order to perfect the whole. It also
places an emphasis on the fact that different levels are distinct.
9. What one practices (qualitative v quantitative)
10. Gladwell explains success as a combination of average/above average talent and luck
to succeed (most successful people have some degree of talent but also tons and tons of
opportunities). Both Gladwell and Chambliss emphasize that opportunities have a large
part in excellence. They differ in that Chambliss doesn’t put as much emphasis on
quantitative practice whereas Gladwell stresses the importance of the “10,000 Hour
Rule”: that practicing 10,000 hours will lead to excellence
11. This is an example of the Matthew Effect. At young ages, kids born around January
have a higher advantage than other kids. The cutoff age for hockey makes it so that these
kids are actually a year older than others on their team. They’re slightly bigger and more
mature than others on their team, and so they receive more recognition and coaching
because it looks like they have more potential. By the time the kids are old enough that
the age difference is irrelevant, these kids have already been given an advantage and had
a chance to better develop their talent and so are more likely to go pro.
12. This has to do with these people coming of age in the perfect area/time period for
development in their field. In the case of the rich Americans, they happened to be born
right at the time where they could come of age in time to take advantage of full structural
innovation in the US and emergence of the prominence of wall street. The computer
billionaires were all born around 1955, because they came of age as computers became
more prominent in society (any later and they would have missed the chance to innovate,
any earlier and the technology for them to work with wouldn’t have existed yet). They
were also given opportunities with computers others weren’t and had a chance to get their
10,000 hours of programming.
13. IQ is not really that important to success because you can be a genius but n