vertica如何，跟impala, hbase,比有什么异同？# Programming - 葵花宝典
a*d
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昨天听到的，当时以为是回到了 April Fools Day
http://www.npr.org/2012/05/03/151860154/put-away-the-bell-curve
Put Away The Bell Curve: Most Of Us Aren't 'Average'
May 3, 2012
For decades, teachers, managers and parents have assumed that the
performance of students and employees fits what's known as the bell curve —
in most activities, we expect a few people to be very good, a few people to
be very bad and most people to be average.
The bell curve powerfully shapes how we think of human performance: If lots
of students or employees happen to show up as extreme outliers — they're
either very good or very bad — we assume they must represent a skewed
sample, because only a few people in a truly random sample are supposed to
be outliers.
New research suggests, however, that rather than describe how humans perform
, the bell curve may actually be constraining how people perform. Minus such
constraints, a new paper argues, lots of people are actually outliers.
Human performance, by this account, does not often fit the bell curve or
what scientists call a normal distribution. Rather, it is more likely to fit
what scientists call a power distribution.
The study examined the performance of 633,263 people involved in four broad
areas of human performance: academics writing papers, athletes at the
professional and collegiate levels, politicians and entertainers.
"We looked at researchers, we looked at entertainers, we looked at
politicians, and we looked at collegiate as well as professional athletes,"
Aguinis said in an interview. "In each of these kinds of industries, we
found that a small minority of superstar performers contribute a
disproportionate amount of the output."
In 186 out of 198 groups ranging from physics professors and Grammy nominees
to cricketers and swimming champions, researchers Ernest O'Boyle Jr., of
Longwood University's College of Business and Economics, and Herman Aguinis
at Indiana University's Kelley School of Business found that a sizable
number in the group were superstars.
These superstars, moreover, accounted for much of the success of the group
as a whole. The vast majority of the others in the group, Aguinis said, were
actually performing below the mathematical average.
More than 80 percent of all Emmy-nominated entertainers, for example, fell
below the mean in terms of the number of nominations they received. A small
but sizable minority, meanwhile, enjoyed outsize success and accounted for a
disproportionately large number of Emmy nominations.
Aguinis said the bell curve may describe human performance in the presence
of some external constraint — such as an assembly line that moved at a
certain speed.
"If you had a superstar performer working at your factory, well, that person
could not do [a] better job than the assembly line would allow," Aguinis
said. "If you unconstrain the situation and allow people to perform as best
as they can, you will see the emergence of a small minority of superstars
who contribute a disproportionate amount of the output."
Aguinis said his findings were descriptive, not prescriptive. He said the
findings should not be interpreted to mean that managers and teachers should
only focus on the superstars and ignore everyone else.
At the same time, he said, successful companies and nations would do well to
identify superstars, because such performers were disproportionately likely
to register new discoveries and achievements.
http://www.npr.org/2012/05/03/151860154/put-away-the-bell-curve
Put Away The Bell Curve: Most Of Us Aren't 'Average'
May 3, 2012
For decades, teachers, managers and parents have assumed that the
performance of students and employees fits what's known as the bell curve —
in most activities, we expect a few people to be very good, a few people to
be very bad and most people to be average.
The bell curve powerfully shapes how we think of human performance: If lots
of students or employees happen to show up as extreme outliers — they're
either very good or very bad — we assume they must represent a skewed
sample, because only a few people in a truly random sample are supposed to
be outliers.
New research suggests, however, that rather than describe how humans perform
, the bell curve may actually be constraining how people perform. Minus such
constraints, a new paper argues, lots of people are actually outliers.
Human performance, by this account, does not often fit the bell curve or
what scientists call a normal distribution. Rather, it is more likely to fit
what scientists call a power distribution.
The study examined the performance of 633,263 people involved in four broad
areas of human performance: academics writing papers, athletes at the
professional and collegiate levels, politicians and entertainers.
"We looked at researchers, we looked at entertainers, we looked at
politicians, and we looked at collegiate as well as professional athletes,"
Aguinis said in an interview. "In each of these kinds of industries, we
found that a small minority of superstar performers contribute a
disproportionate amount of the output."
In 186 out of 198 groups ranging from physics professors and Grammy nominees
to cricketers and swimming champions, researchers Ernest O'Boyle Jr., of
Longwood University's College of Business and Economics, and Herman Aguinis
at Indiana University's Kelley School of Business found that a sizable
number in the group were superstars.
These superstars, moreover, accounted for much of the success of the group
as a whole. The vast majority of the others in the group, Aguinis said, were
actually performing below the mathematical average.
More than 80 percent of all Emmy-nominated entertainers, for example, fell
below the mean in terms of the number of nominations they received. A small
but sizable minority, meanwhile, enjoyed outsize success and accounted for a
disproportionately large number of Emmy nominations.
Aguinis said the bell curve may describe human performance in the presence
of some external constraint — such as an assembly line that moved at a
certain speed.
"If you had a superstar performer working at your factory, well, that person
could not do [a] better job than the assembly line would allow," Aguinis
said. "If you unconstrain the situation and allow people to perform as best
as they can, you will see the emergence of a small minority of superstars
who contribute a disproportionate amount of the output."
Aguinis said his findings were descriptive, not prescriptive. He said the
findings should not be interpreted to mean that managers and teachers should
only focus on the superstars and ignore everyone else.
At the same time, he said, successful companies and nations would do well to
identify superstars, because such performers were disproportionately likely
to register new discoveries and achievements.
