Questões de Vestibular Sobre inglês
Foram encontradas 6.020 questões
Q1262960
Inglês
Texto associado
Read the following passage and choose the option which best completes each question, according to the
text:
Footfalls
London is a city made for walking. Unlike, for example, Los Angeles its centre is easily accessible on foot.
Between 2001 and 2011 the number of trips made daily on foot in London increased by 12%. Each day 6.2m walks
are made across the city.
Several reasons account for the walking boom. The number of Londoners increased by 12% from 7.3m in
2001 to 8.2m in 2011, and Underground trains are hot and overcrowded. But other factors also encourage
pedestrians. In 2004 Ken Livingstone, then mayor of London, promised to make London a “walkable city”. Some of
his plans were carried on by Boris Johnson, the current mayor. These include a scheme to create clearly-marked
maps for use across the city and make streets more pedestrian-friendly. Londoners may also be more aware of the
advantages of walking. Health campaigns like the National Health Service’s “Live Well” emphasize that walking is
the easiest form of exercise.
High streets and town centres need to win back walkers. Learning from London’s incentives could be a start.
(Adapted from: http://www.economist.com/news/britain/21582576-urban-pedestrians-buck-national-trend-footfalls.)
The word unlike in “Unlike, for instance, Los Angeles…” (paragraph 01) indicates that
Q1262176
Inglês
Texto associado
Read the text below to answer question.
Whaling Today
By Meghan E. Marrero and Stuart Thornton
Tuesday, November 1, 2011
In 1946, several countries joined to form the International
Whaling Commission (IWC). The IWC’s purpose is to prevent
overhunting of whales. Its original regulations, however, were loose,
and quotas were high. Whale stocks continued to decline. The IWC
eventually established whaling-free sanctuaries in the Indian Ocean
(1979) and the ocean surrounding Antarctica (1994).
The IWC called for a moratorium on commercial whaling in
1982. Both Japan and Norway voted against this policy. Today,
Norway supports hunting minke whales for meat. Japan allows whaling
for scientific purposes, although many experts question if more whales
are taken than are necessary. Meat from whales killed for research is
sold as food.
Many species of whale have benefitted from the IWC’s
moratorium. Dave Weller, a research biologist at NOAA’s Southwest
Fisheries Science Center in La Jolla, California, says the eastern
Pacific gray whale population has recovered.
“I think there is pretty good evidence that a moratorium on
hunting has allowed certain populations to recover from depleted
status when they were being whaled,” he says.
According to Weller, the IWC’s moratorium on whale hunting
is one of two major steps the organization is taking.
“The other thing that the IWC has very successfully done is
to collect information and provide analysis of data to help us
understand the status of various populations that in some cases we
knew very little about,” he says.
Despite the general moratorium, limited whaling is permitted
to indigenous cultures.
“In the United States, the Inuit Eskimos in the north slope of
Alaska, in Barrow, Alaska, still hunt for bowhead whales,” Weller says.
“There is a request by the Makah Indian tribe, which is in northern
Washington state, to resume gray whale hunting, which they had
traditionally done. But that’s pending deliberations right now.”
Source: http://education.nationalgeographic.com/education/news/
(Adapted)
Mark the CORRECT alternative, according to the text.
Q1262175
Inglês
Texto associado
Read the text below to answer question.
Whaling Today
By Meghan E. Marrero and Stuart Thornton
Tuesday, November 1, 2011
In 1946, several countries joined to form the International
Whaling Commission (IWC). The IWC’s purpose is to prevent
overhunting of whales. Its original regulations, however, were loose,
and quotas were high. Whale stocks continued to decline. The IWC
eventually established whaling-free sanctuaries in the Indian Ocean
(1979) and the ocean surrounding Antarctica (1994).
The IWC called for a moratorium on commercial whaling in
1982. Both Japan and Norway voted against this policy. Today,
Norway supports hunting minke whales for meat. Japan allows whaling
for scientific purposes, although many experts question if more whales
are taken than are necessary. Meat from whales killed for research is
sold as food.
Many species of whale have benefitted from the IWC’s
moratorium. Dave Weller, a research biologist at NOAA’s Southwest
Fisheries Science Center in La Jolla, California, says the eastern
Pacific gray whale population has recovered.
“I think there is pretty good evidence that a moratorium on
hunting has allowed certain populations to recover from depleted
status when they were being whaled,” he says.
According to Weller, the IWC’s moratorium on whale hunting
is one of two major steps the organization is taking.
“The other thing that the IWC has very successfully done is
to collect information and provide analysis of data to help us
understand the status of various populations that in some cases we
knew very little about,” he says.
Despite the general moratorium, limited whaling is permitted
to indigenous cultures.
“In the United States, the Inuit Eskimos in the north slope of
Alaska, in Barrow, Alaska, still hunt for bowhead whales,” Weller says.
“There is a request by the Makah Indian tribe, which is in northern
Washington state, to resume gray whale hunting, which they had
traditionally done. But that’s pending deliberations right now.”
Source: http://education.nationalgeographic.com/education/news/
(Adapted)
According to the text, judge the items below as true (T) or
false (F).
I. In 1946, a group of national governments formed the IWC in order to collaborate with the killing and hunting of whales for commercial purposes. II. The original regulations of IWC were not really helpful. III. The IWC does not make any exception for whaling. IV. The IWC requested a moratorium on commercial whaling in 1982. V. Japan and Norway completely agreed with the policy proposed by IWC.
Mark the correct option.
I. In 1946, a group of national governments formed the IWC in order to collaborate with the killing and hunting of whales for commercial purposes. II. The original regulations of IWC were not really helpful. III. The IWC does not make any exception for whaling. IV. The IWC requested a moratorium on commercial whaling in 1982. V. Japan and Norway completely agreed with the policy proposed by IWC.
Mark the correct option.
Q1262174
Inglês
Is age the cause of receding gums? By Claudia Hammond.
The phrase “long in the tooth” comes from the practice of gauging a horse’s age by the length of its teeth. Nineteenth century horse-traders were not a particularly trustworthy bunch, so a wise buyer would often check inside the animal’s mouth. If the teeth looked long it meant its gums had already receded, suggesting the potential purchase might be older than claimed. This might have served people well when it came to buying horses, but what about humans? Gingival recession, as it’s formally known, is more common amongst the elderly. A US study of almost 10,000 people found that 38% of people aged 30-39 had some degree of the condition, compared with 71% in the 50-59 age group, and 90% for those aged between 80-90. However that doesn’t mean ageing in itself is the cause. It’s a long process that can start in your teens, and one that can be triggered by various factors. In some cases, there is nothing people can do to reduce their chances of developing the condition. Some people inherit thin and fragile gums which recede more easily. Others have teeth which are overcrowded or stick out, meaning that there’s not enough jawbone to cover the root of the tooth. Dental hygiene also plays a big role. Plaque, consisting of a sticky film of bacteria, is constantly forming on our teeth. Failure to clear the build ups through brushing and flossing can lead to gum disease. If left untreated, one possible complication is the destruction of the bone around the teeth and the gum tissue in which they sit. As the tissue recedes, the root of the tooth is exposed, making it appear longer. Then there’s the way you brush your teeth. If you use a sawing action with a hard brush, there’s a danger of gradually wearing away the gum. For this reason dentists tend to advise brushing in small circles with a soft brush or using an electric toothbrush to prevent you from pressing so hard. The damage accumulates over time, causing the gums to recede imperceptibly, until one day you look in the mirror and realise you’ve changed. As this transformation can take decades, many people assume it’s a natural part of the ageing process. Research on receding gums often relies on asking people what kind of toothbrush they use, the brushing motions they use and how hard they brush. Some argue that due to a lack of controlled studies, there’s no definitive evidence that hard brushing does anything more than cause temporary abrasions, but many dentists do consider there to be a link. The condition is also more common in smokers. With so many different factors involved, controlled studies are difficult to do. Many are cross-sectional, meaning they take a snapshot in time. So if you’re looking to buy a horse it might be worth their checking their teeth, but ageing is not a direct cause of receding gums. It’s simply that the damage accumulates and becomes more obvious over time. Source: http://www.bbc.com (Adapted) According to the text, it is INCORRECT to say
The phrase “long in the tooth” comes from the practice of gauging a horse’s age by the length of its teeth. Nineteenth century horse-traders were not a particularly trustworthy bunch, so a wise buyer would often check inside the animal’s mouth. If the teeth looked long it meant its gums had already receded, suggesting the potential purchase might be older than claimed. This might have served people well when it came to buying horses, but what about humans? Gingival recession, as it’s formally known, is more common amongst the elderly. A US study of almost 10,000 people found that 38% of people aged 30-39 had some degree of the condition, compared with 71% in the 50-59 age group, and 90% for those aged between 80-90. However that doesn’t mean ageing in itself is the cause. It’s a long process that can start in your teens, and one that can be triggered by various factors. In some cases, there is nothing people can do to reduce their chances of developing the condition. Some people inherit thin and fragile gums which recede more easily. Others have teeth which are overcrowded or stick out, meaning that there’s not enough jawbone to cover the root of the tooth. Dental hygiene also plays a big role. Plaque, consisting of a sticky film of bacteria, is constantly forming on our teeth. Failure to clear the build ups through brushing and flossing can lead to gum disease. If left untreated, one possible complication is the destruction of the bone around the teeth and the gum tissue in which they sit. As the tissue recedes, the root of the tooth is exposed, making it appear longer. Then there’s the way you brush your teeth. If you use a sawing action with a hard brush, there’s a danger of gradually wearing away the gum. For this reason dentists tend to advise brushing in small circles with a soft brush or using an electric toothbrush to prevent you from pressing so hard. The damage accumulates over time, causing the gums to recede imperceptibly, until one day you look in the mirror and realise you’ve changed. As this transformation can take decades, many people assume it’s a natural part of the ageing process. Research on receding gums often relies on asking people what kind of toothbrush they use, the brushing motions they use and how hard they brush. Some argue that due to a lack of controlled studies, there’s no definitive evidence that hard brushing does anything more than cause temporary abrasions, but many dentists do consider there to be a link. The condition is also more common in smokers. With so many different factors involved, controlled studies are difficult to do. Many are cross-sectional, meaning they take a snapshot in time. So if you’re looking to buy a horse it might be worth their checking their teeth, but ageing is not a direct cause of receding gums. It’s simply that the damage accumulates and becomes more obvious over time. Source: http://www.bbc.com (Adapted) According to the text, it is INCORRECT to say
Q1262173
Inglês
Is age the cause of receding gums?
By Claudia Hammond.
The phrase “long in the tooth” comes from the practice of gauging a horse’s age by the length of its teeth. Nineteenth century horse-traders were not a particularly trustworthy bunch, so a wise buyer would often check inside the animal’s mouth. If the teeth looked long it meant its gums had already receded, suggesting the potential purchase might be older than claimed. This might have served people well when it came to buying horses, but what about humans? Gingival recession, as it’s formally known, is more common amongst the elderly. A US study of almost 10,000 people found that 38% of people aged 30-39 had some degree of the condition, compared with 71% in the 50-59 age group, and 90% for those aged between 80-90. However that doesn’t mean ageing in itself is the cause. It’s a long process that can start in your teens, and one that can be triggered by various factors. In some cases, there is nothing people can do to reduce their chances of developing the condition. Some people inherit thin and fragile gums which recede more easily. Others have teeth which are overcrowded or stick out, meaning that there’s not enough jawbone to cover the root of the tooth. Dental hygiene also plays a big role. Plaque, consisting of a sticky film of bacteria, is constantly forming on our teeth. Failure to clear the build ups through brushing and flossing can lead to gum disease. If left untreated, one possible complication is the destruction of the bone around the teeth and the gum tissue in which they sit. As the tissue recedes, the root of the tooth is exposed, making it appear longer. Then there’s the way you brush your teeth. If you use a sawing action with a hard brush, there’s a danger of gradually wearing away the gum. For this reason dentists tend to advise brushing in small circles with a soft brush or using an electric toothbrush to prevent you from pressing so hard. The damage accumulates over time, causing the gums to recede imperceptibly, until one day you look in the mirror and realise you’ve changed. As this transformation can take decades, many people assume it’s a natural part of the ageing process. Research on receding gums often relies on asking people what kind of toothbrush they use, the brushing motions they use and how hard they brush. Some argue that due to a lack of controlled studies, there’s no definitive evidence that hard brushing does anything more than cause temporary abrasions, but many dentists do consider there to be a link. The condition is also more common in smokers. With so many different factors involved, controlled studies are difficult to do. Many are cross-sectional, meaning they take a snapshot in time. So if you’re looking to buy a horse it might be worth their checking their teeth, but ageing is not a direct cause of receding gums. It’s simply that the damage accumulates and becomes more obvious over time. Source: http://www.bbc.com (Adapted)
According to the text, judge the items below as true (T) or false (F).
I. Nineteenth century horse-traders were reliable people. II. A buyer who would check the horse's gums before buying it, was not considered a clever person. III. Although it is more observed amongst the elderly, gingival recession can begin during youth. IV. The phrase “long in the tooth” is related to the practice of determining a horse's age, and therefore its value, by examining its teeth. V. People can always prevent the development of gingival recession, once it is never possible for them to inherited sensitive gums.
Mark the correct option:
The phrase “long in the tooth” comes from the practice of gauging a horse’s age by the length of its teeth. Nineteenth century horse-traders were not a particularly trustworthy bunch, so a wise buyer would often check inside the animal’s mouth. If the teeth looked long it meant its gums had already receded, suggesting the potential purchase might be older than claimed. This might have served people well when it came to buying horses, but what about humans? Gingival recession, as it’s formally known, is more common amongst the elderly. A US study of almost 10,000 people found that 38% of people aged 30-39 had some degree of the condition, compared with 71% in the 50-59 age group, and 90% for those aged between 80-90. However that doesn’t mean ageing in itself is the cause. It’s a long process that can start in your teens, and one that can be triggered by various factors. In some cases, there is nothing people can do to reduce their chances of developing the condition. Some people inherit thin and fragile gums which recede more easily. Others have teeth which are overcrowded or stick out, meaning that there’s not enough jawbone to cover the root of the tooth. Dental hygiene also plays a big role. Plaque, consisting of a sticky film of bacteria, is constantly forming on our teeth. Failure to clear the build ups through brushing and flossing can lead to gum disease. If left untreated, one possible complication is the destruction of the bone around the teeth and the gum tissue in which they sit. As the tissue recedes, the root of the tooth is exposed, making it appear longer. Then there’s the way you brush your teeth. If you use a sawing action with a hard brush, there’s a danger of gradually wearing away the gum. For this reason dentists tend to advise brushing in small circles with a soft brush or using an electric toothbrush to prevent you from pressing so hard. The damage accumulates over time, causing the gums to recede imperceptibly, until one day you look in the mirror and realise you’ve changed. As this transformation can take decades, many people assume it’s a natural part of the ageing process. Research on receding gums often relies on asking people what kind of toothbrush they use, the brushing motions they use and how hard they brush. Some argue that due to a lack of controlled studies, there’s no definitive evidence that hard brushing does anything more than cause temporary abrasions, but many dentists do consider there to be a link. The condition is also more common in smokers. With so many different factors involved, controlled studies are difficult to do. Many are cross-sectional, meaning they take a snapshot in time. So if you’re looking to buy a horse it might be worth their checking their teeth, but ageing is not a direct cause of receding gums. It’s simply that the damage accumulates and becomes more obvious over time. Source: http://www.bbc.com (Adapted)
According to the text, judge the items below as true (T) or false (F).
I. Nineteenth century horse-traders were reliable people. II. A buyer who would check the horse's gums before buying it, was not considered a clever person. III. Although it is more observed amongst the elderly, gingival recession can begin during youth. IV. The phrase “long in the tooth” is related to the practice of determining a horse's age, and therefore its value, by examining its teeth. V. People can always prevent the development of gingival recession, once it is never possible for them to inherited sensitive gums.
Mark the correct option:
Q1262172
Inglês
According to the cartoon below it is CORRECT to affirm.
Source: www.glasbergen.com
Source: www.glasbergen.com
Q1262171
Inglês
According to the cartoon below, judge the following statements
as true (T) or false (F).
Source: http://eoienglishclub.wikispaces.com/ENGLISH+B1/unit3
I. The girl’s sentence can be transcript as “See you. I'll text you later”. II. Young people do not make difference between spoken and written speech. III. The old man can’t realize young people play with the sound of the words. IV. Young people text so much, they adequate their speech according to the facilities of keyboards. V. Language changes from one generation to another.
Choose the CORRECT alternative.
Source: http://eoienglishclub.wikispaces.com/ENGLISH+B1/unit3
I. The girl’s sentence can be transcript as “See you. I'll text you later”. II. Young people do not make difference between spoken and written speech. III. The old man can’t realize young people play with the sound of the words. IV. Young people text so much, they adequate their speech according to the facilities of keyboards. V. Language changes from one generation to another.
Choose the CORRECT alternative.
Q1262170
Inglês
Texto associado
Read the text below to answer question.
Pope Francis: Who am I to judge gay people?
By David Willey BBC News, Rome
Pope Francis, the first ever pontiff from Latin America,
has struck an unusual new tone. Now he is back at his desk in
his modest Vatican quarters, he has some important decisions
to make about the future governance of his Church. Normally
the cardinals who run the Holy See are off on their long summer
holidays at this time of year. But Pope Francis' seasons are not
the same as those of his predecessors. In the Southern
Hemisphere, where the bulk of his international flock now lives,
it is winter.
Pope Francis plans to spend the month of August
preparing for some radical changes in the future governance of
his worldwide Church. Be prepared for some big surprises. His
remarks on gay people are being seen as much less
judgemental than his predecessor's position on the issue. Pope Benedict XVI signed a document in 2005 that said men with
deep-rooted homosexual tendencies should not be priests. But
Pope Francis said gay clergymen should be forgiven and their
sins forgotten.
"The Catechism of the Catholic Church explains this
very well," Pope Francis said in a wide-ranging 80-minute long
interview with Vatican journalists."It says they should not be
marginalised because of this but that they must be integrated
into society."But he condemned what he described as lobbying
by gay people. "The problem is not having this orientation," he
said. "We must be brothers. The problem is lobbying by this
orientation, or lobbies of greedy people, political lobbies,
Masonic lobbies, so many lobbies. This is the worse problem."
Source: http://www.bbc.co.uk/news/world-europe-23489702. Adapted.
According to the text, why Pope Francis does not feel
comfortable to judge gay people?
Q1262169
Inglês
Texto associado
Read the text below to answer question.
Pope Francis: Who am I to judge gay people?
By David Willey BBC News, Rome
Pope Francis, the first ever pontiff from Latin America,
has struck an unusual new tone. Now he is back at his desk in
his modest Vatican quarters, he has some important decisions
to make about the future governance of his Church. Normally
the cardinals who run the Holy See are off on their long summer
holidays at this time of year. But Pope Francis' seasons are not
the same as those of his predecessors. In the Southern
Hemisphere, where the bulk of his international flock now lives,
it is winter.
Pope Francis plans to spend the month of August
preparing for some radical changes in the future governance of
his worldwide Church. Be prepared for some big surprises. His
remarks on gay people are being seen as much less
judgemental than his predecessor's position on the issue. Pope Benedict XVI signed a document in 2005 that said men with
deep-rooted homosexual tendencies should not be priests. But
Pope Francis said gay clergymen should be forgiven and their
sins forgotten.
"The Catechism of the Catholic Church explains this
very well," Pope Francis said in a wide-ranging 80-minute long
interview with Vatican journalists."It says they should not be
marginalised because of this but that they must be integrated
into society."But he condemned what he described as lobbying
by gay people. "The problem is not having this orientation," he
said. "We must be brothers. The problem is lobbying by this
orientation, or lobbies of greedy people, political lobbies,
Masonic lobbies, so many lobbies. This is the worse problem."
Source: http://www.bbc.co.uk/news/world-europe-23489702. Adapted.
According to the text, judge the following statements as
true (T) or false (F).
I. Pope Francis will bring big surprises in August.
II. Pope Benedict XVI was against homosexual priests.
III. The Catechism of the Catholic Church explains the
difference from being homosexual and in lobbying
homosexuality.
IV. Pope Francis disapproves any kind of lobbies.
V. Pope Francis is indifferent about gay people.
Choose the CORRECT alternative.
Choose the CORRECT alternative.
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261842
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
In the following question, some sentences from the text may have been modified to fit certain grammatical structures.
The correct form that completes the ifclause “If students had to learn to communicate their findings,” is “they __________________.”
The correct form that completes the ifclause “If students had to learn to communicate their findings,” is “they __________________.”
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261841
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
In the following question, some sentences from the text may have been modified to fit certain grammatical structures.
The sentence “There will be almost half a million jobs in five years.” in the conditional form would be
The sentence “There will be almost half a million jobs in five years.” in the conditional form would be
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261840
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
In the following question, some sentences from the text may have been modified to fit certain grammatical structures.
The sentences “…they know it will make them employable.” and “…Amazon tells them what books they should read” contain, respectively, a/an
The sentences “…they know it will make them employable.” and “…Amazon tells them what books they should read” contain, respectively, a/an
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261839
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
In the following question, some sentences
from the text may have been modified to fit
certain grammatical structures.
The sentences “Ethics classes address these questions.” and “The United States will need a great number of graduates with skills handling large amounts of data.” contain, respectively, a/an
The sentences “Ethics classes address these questions.” and “The United States will need a great number of graduates with skills handling large amounts of data.” contain, respectively, a/an
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261838
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
In the sentences “The field has been
spawned by the enormous amounts of data” and
“The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics”, the verb forms are respectively
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261837
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
In the sentences “We’re building these
models that have impact on human life.” and “She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service.” one finds, respectively, a/an
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261836
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
The sentence “She might, for example,
analyze tax return data to develop algorithms that
flag fraudulent filings.” contains
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261835
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
The sentences “In the fall, Columbia will offer
new master’s and certificate programs heavy on
data.” and “Data scientists are the magicians of the
Big Data era.” contain, respectively, at least one
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261834
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
In the sentences “…this is an academic
interest with real-world applications,” said Chris
Wiggins, a professor of applied mathematics at
Columbia who is involved in its new Institute for
Data Sciences and Engineering.” and “This is a
generation of kids that grew up with data science
around them.”, one finds adjective clauses that are
respectively
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261833
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
The sentences “Many use data sets provided
by businesses or government, and pass back their
results.” and “Because data science is so new,
universities are scrambling to define it…” contain,
respectively, a
Ano: 2013
Banca:
UECE-CEV
Órgão:
UECE
Prova:
UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261832
Inglês
Texto associado
TEXT
HARVARD BUSINESS REVIEW calls data
science “the sexiest job in the 21st century,” and by
most accounts this hot new field promises to
revolutionize industries from business to
government, health care to academia.
The field has been spawned by the
enormous amounts of data that modern technologies
create — be it the online behavior of Facebook
users, tissue samples of cancer patients,
purchasing habits of grocery shoppers or crime
statistics of cities. Data scientists are the magicians
of the Big Data era. They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it, then
suggest how to use the information to make
decisions.
In the last few years, dozens of programs
under a variety of names have sprung up in
response to the excitement about Big Data, not to
mention the six-figure salaries for some recent
graduates. In the fall, Columbia will offer new
master’s and certificate programs heavy on data.
The University of San Francisco will soon graduate
its charter class of students with a master’s in
analytics.
Rachel Schutt, a senior research scientist at
Johnson Research Labs, taught “Introduction to Data
Science” last semester at Columbia (its first course
with “data science” in the title). She described the
data scientist this way: “a hybrid computer scientist
software engineer statistician.” And added: “The
best tend to be really curious people, thinkers who
ask good questions and are O.K. dealing with
unstructured situations and trying to find structure
in them.”
Eurry Kim, a 30-year-old “wannabe data
scientist,” is studying at Columbia for a master’s in
quantitative methods in the social sciences and
plans to use her degree for government service. She
discovered the possibilities while working as a
corporate tax analyst at the Internal Revenue
Service. She might, for example, analyze tax return
data to develop algorithms that flag fraudulent
filings, or cull national security databases to spot
suspicious activity.
Some of her classmates are hoping to apply
their skills to e-commerce, where data about users’
browsing history is gold.
“This is a generation of kids that grew up
with data science around them — Netflix telling
them what movies they should watch, Amazon
telling them what books they should read — so this
is an academic interest with real-world applications,”
said Chris Wiggins, a professor of applied
mathematics at Columbia who is involved in its new
Institute for Data Sciences and Engineering. “And,”
he added, “they know it will make them
employable.”
Universities can hardly turn out data
scientists fast enough. To meet demand from employers, the United States will need to increase
the number of graduates with skills handling large
amounts of data by as much as 60 percent,
according to a report by McKinsey Global Institute.
There will be almost half a million jobs in five
years, and a shortage of up to 190,000 qualified
data scientists, plus a need for 1.5 million
executives and support staff who have an
understanding of data.
Because data science is so new,
universities are scrambling to define it and develop
curriculums. As an academic field, it cuts across
disciplines, with courses in statistics, analytics,
computer science and math, coupled with the
specialty a student wants to analyze, from patterns
in marine life to historical texts.
With the sheer volume, variety and speed
of data today, as well as developing technologies,
programs are more than a repackaging of existing
courses. “Data science is emerging as an academic
discipline, defined not by a mere amalgamation of
interdisciplinary fields but as a body of knowledge,
a set of professional practices, a professional
organization and a set of ethical responsibilities,”
said Christopher Starr, chairman of the computer
science department at the College of Charleston,
one of a few institutions offering data science at
the undergraduate level.
Most master’s degree programs in data
science require basic programming skills. They
start with what Ms. Schutt describes as the
“boring” part — scraping and cleaning raw data
and “getting it into a nice table where you can
actually analyze it.” Many use data sets provided
by businesses or government, and pass back their
results. Some host competitions to see which
student can come up with the best solution to a
company’s problem.
Studying a Web user’s data has privacy
implications. Using data to decide someone’s
eligibility for a line of credit or health insurance, or
even recommending who they friend on
Facebook, can affect their lives. “We’re building
these models that have impact on human life,” Ms.
Schutt said. “How can we do that carefully?” Ethics
classes address these questions.
Finally, students have to learn to
communicate their findings, visually and orally,
and they need business know-how, perhaps to
develop new products.
From: www.nytimes.com
The sentences “They crunch the data, use
mathematical models to analyze it and create
narratives or visualizations to explain it…” and “In
the last few years, dozens of programs under a
variety of names have sprung up in response to the
excitement about Big Data...” should be classified
respectively as
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