Questões de Vestibular de Inglês - Interpretação de texto | Reading comprehension

Foram encontradas 4.863 questões

Ano: 2016 Banca: UNIOESTE Órgão: UNIOESTE Prova: UNIOESTE - 2016 - UNIOESTE - Vestibular - Manhã |
Q1261936 Inglês

O texto a seguir se refere a questão.


Challenges concerning multiculturalism in Canada

   The official Canadian policy of multiculturalism has been updated twice since its introduction in 1971. It was originally created as a policy based on the logic of ethnicity, modified to deal with racism and amended to include freedom of religion. In 1988 the Canadian Multiculturalism Act was passed. 

   Canada is considered a nation of immigrants such that cultural diversity is often presented as the essence of national identity. However, it is difficult to negotiate social and political policy when trying to speak for such a varied populace. Two very real challenges that Canada faces in regard to multiculturalism are the clash of cultures and the socioeconomic position of immigrants.

    An example of clash of cultures is the one between English and French-Canada. The province of Quebec has always asserted a distinct identity and an inclination towards separatism from the rest of the country. In 1995, there was a referendum in the province of Quebec concerning separation in which 49% of the voting population voted “yes” and 51% voted “no”. The clash between French and English-Canada is primarily a cultural clash with Quebec concerned with preserving its own history, language and values; fearing these things are apt to become lost within English-Canada. Since the referendum, tensions have cooled a bit and Canada’s national administration has increased their efforts to accommodate Quebec identity within a Canadian identity.

     Another challenge of multiculturalism is the socioeconomic position of immigrants. Diversity is supported by governmental policy but Canada is still a society where racist interactions and poor-bashing are severely detrimental to minorities (especially recent arrivals). There are many barriers to equal integration, especially in education, housing and employment. For example, in the workforce it is very difficult to get a job when the potential employer feels you are not speaking “proper” English or you do not have any Canadian work experience on your resumé. This often leads to overqualified people in full-time minimum wage positions with little or no benefits and no access, time or funds for language classes or other training programs. These sorts of circumstances lead to isolation, alienation, poverty and unsafe environments where a new immigrant does not feel safe to report or act against harassment or abuse.

Source: Adapted from http://globalcitizens.pbworks.com/w/page/9036226/Challenges%20Concerning%20Multiculturalism%20in%20Canada.


Mark the CORRECT alternative.
Alternativas
Ano: 2016 Banca: UNIOESTE Órgão: UNIOESTE Prova: UNIOESTE - 2016 - UNIOESTE - Vestibular - Manhã |
Q1261934 Inglês

O texto a seguir se refere a questão.


Challenges concerning multiculturalism in Canada

   The official Canadian policy of multiculturalism has been updated twice since its introduction in 1971. It was originally created as a policy based on the logic of ethnicity, modified to deal with racism and amended to include freedom of religion. In 1988 the Canadian Multiculturalism Act was passed. 

   Canada is considered a nation of immigrants such that cultural diversity is often presented as the essence of national identity. However, it is difficult to negotiate social and political policy when trying to speak for such a varied populace. Two very real challenges that Canada faces in regard to multiculturalism are the clash of cultures and the socioeconomic position of immigrants.

    An example of clash of cultures is the one between English and French-Canada. The province of Quebec has always asserted a distinct identity and an inclination towards separatism from the rest of the country. In 1995, there was a referendum in the province of Quebec concerning separation in which 49% of the voting population voted “yes” and 51% voted “no”. The clash between French and English-Canada is primarily a cultural clash with Quebec concerned with preserving its own history, language and values; fearing these things are apt to become lost within English-Canada. Since the referendum, tensions have cooled a bit and Canada’s national administration has increased their efforts to accommodate Quebec identity within a Canadian identity.

     Another challenge of multiculturalism is the socioeconomic position of immigrants. Diversity is supported by governmental policy but Canada is still a society where racist interactions and poor-bashing are severely detrimental to minorities (especially recent arrivals). There are many barriers to equal integration, especially in education, housing and employment. For example, in the workforce it is very difficult to get a job when the potential employer feels you are not speaking “proper” English or you do not have any Canadian work experience on your resumé. This often leads to overqualified people in full-time minimum wage positions with little or no benefits and no access, time or funds for language classes or other training programs. These sorts of circumstances lead to isolation, alienation, poverty and unsafe environments where a new immigrant does not feel safe to report or act against harassment or abuse.

Source: Adapted from http://globalcitizens.pbworks.com/w/page/9036226/Challenges%20Concerning%20Multiculturalism%20in%20Canada.


Assinale a alternativa que contém a ideia central do texto.
Alternativas
Ano: 2016 Banca: UNIOESTE Órgão: UNIOESTE Prova: UNIOESTE - 2016 - UNIOESTE - Vestibular - Manhã |
Q1261933 Inglês

O texto a seguir se refere à questão.

Fonte: https://garfield.com/comic/2016/05/22

Imagem associada para resolução da questão

De acordo com o texto, é CORRETO afirmar que

Alternativas
Ano: 2016 Banca: UNIOESTE Órgão: UNIOESTE Prova: UNIOESTE - 2016 - UNIOESTE - Vestibular - Manhã |
Q1261932 Inglês

O texto a seguir se refere a questão.

What's wrong with buying fake luxury goods?

By Bethan Bell, BBC News, 15 July 2016

Every time a new haul of fake designer goods is seized we're told that the people who buy them are ruining the reputation of brands, stealing revenue from companies, contributing to an unethical labour market and subsidising organised crime. But is this really the case?  

     A BBC investigation has found over the past two years, thousands of fake goods were seized from black markets across England.

    But is there any harm in nabbing a pair of "Louboutins" from a market, or a "Chanel" handbag from a chap selling them on a foreign beach? To the average punter it might sound a bit far-fetched that their cash goes straight to a drugs cartel or gun-runners.

   We're not talking about alcohol, tobacco or medications - buying such items clearly poses a health risk. The same can be said for toys which aren't up to safety standards, and sunglasses which don't have the recommended UV protection. Nor are we talking about people who genuinely believe the goods they buy are the real thing. 

    We're talking about those who are happy to get knock-off designer items for knock-down prices. The people who are well aware there may be issues about quality and copyright - but don't actually mind.

     After all, are the people who buy fakes for a tenner really depriving the companies that sell goods for hundreds or even thousands of pounds? A woman who makes an impulse buy in a market almost certainly wouldn't otherwise invest in the real deal, while the wealthy buyers of the genuine brand pride themselves on knowing the difference and having the official article.

Fonte: http://www.bbc.com/news/uk-england-36782724

Considerando o contexto, assinale a alternativa que melhor traduz o trecho “Every time a new haul of fake designer goods is seized...”.
Alternativas
Ano: 2016 Banca: UNIOESTE Órgão: UNIOESTE Prova: UNIOESTE - 2016 - UNIOESTE - Vestibular - Manhã |
Q1261931 Inglês

O texto a seguir se refere a questão.

What's wrong with buying fake luxury goods?

By Bethan Bell, BBC News, 15 July 2016

Every time a new haul of fake designer goods is seized we're told that the people who buy them are ruining the reputation of brands, stealing revenue from companies, contributing to an unethical labour market and subsidising organised crime. But is this really the case?  

     A BBC investigation has found over the past two years, thousands of fake goods were seized from black markets across England.

    But is there any harm in nabbing a pair of "Louboutins" from a market, or a "Chanel" handbag from a chap selling them on a foreign beach? To the average punter it might sound a bit far-fetched that their cash goes straight to a drugs cartel or gun-runners.

   We're not talking about alcohol, tobacco or medications - buying such items clearly poses a health risk. The same can be said for toys which aren't up to safety standards, and sunglasses which don't have the recommended UV protection. Nor are we talking about people who genuinely believe the goods they buy are the real thing. 

    We're talking about those who are happy to get knock-off designer items for knock-down prices. The people who are well aware there may be issues about quality and copyright - but don't actually mind.

     After all, are the people who buy fakes for a tenner really depriving the companies that sell goods for hundreds or even thousands of pounds? A woman who makes an impulse buy in a market almost certainly wouldn't otherwise invest in the real deal, while the wealthy buyers of the genuine brand pride themselves on knowing the difference and having the official article.

Fonte: http://www.bbc.com/news/uk-england-36782724

No texto, o autor afirma que
Alternativas
Ano: 2016 Banca: UNIOESTE Órgão: UNIOESTE Prova: UNIOESTE - 2016 - UNIOESTE - Vestibular - Manhã |
Q1261930 Inglês

O texto a seguir se refere a questão.

What's wrong with buying fake luxury goods?

By Bethan Bell, BBC News, 15 July 2016

Every time a new haul of fake designer goods is seized we're told that the people who buy them are ruining the reputation of brands, stealing revenue from companies, contributing to an unethical labour market and subsidising organised crime. But is this really the case?  

     A BBC investigation has found over the past two years, thousands of fake goods were seized from black markets across England.

    But is there any harm in nabbing a pair of "Louboutins" from a market, or a "Chanel" handbag from a chap selling them on a foreign beach? To the average punter it might sound a bit far-fetched that their cash goes straight to a drugs cartel or gun-runners.

   We're not talking about alcohol, tobacco or medications - buying such items clearly poses a health risk. The same can be said for toys which aren't up to safety standards, and sunglasses which don't have the recommended UV protection. Nor are we talking about people who genuinely believe the goods they buy are the real thing. 

    We're talking about those who are happy to get knock-off designer items for knock-down prices. The people who are well aware there may be issues about quality and copyright - but don't actually mind.

     After all, are the people who buy fakes for a tenner really depriving the companies that sell goods for hundreds or even thousands of pounds? A woman who makes an impulse buy in a market almost certainly wouldn't otherwise invest in the real deal, while the wealthy buyers of the genuine brand pride themselves on knowing the difference and having the official article.

Fonte: http://www.bbc.com/news/uk-england-36782724

De acordo com o texto, marque a alternativa que menciona produto(s) falsificado(s) que, ao ser(em) utilizado(s) pelo consumidor, não oferece(m) risco.
Alternativas
Ano: 2010 Banca: PUC - Campinas Órgão: PUC - Campinas Prova: PUC - Campinas - 2010 - PUC - Campinas - Vestibular |
Q1261922 Inglês

Instruções: Leia atentamente o texto abaixo para responder a questão.


Banana, a fruta mais consumida e perigosa do mundo


(Adaptado de Sergio Augusto, O Estado de S. Paulo, 26/04/2008)

English term or phrase: banana bender
I know what it means, ie Queenslander, but I don't understand if it really implies that the bananas grown in Queensland are straight and have therefore to be bent. I found this information in a couple of websites (eg http://archiver.rootsweb.com/th/read/HAMPSHIRELIFE/2001-12)... yet I suspect it is a joke. Thanks a lot in advance.
Just a thought − John Explanation: Hi John, 
Since you already know that this is indeed a slang term for a Queenslander, and that it is in fact a joke and probably a racial slur, I was thinking it may be referring to a pointless act. As far as I know all bananas are already bent, so to be a banana bender is foolish and unnecessary.  Let's suppose that the bananas in Queensland do grow straight. Why on Earth would someone want to bend them? If the expression is meant to be an "insult" it's probably suggesting that a Queenslander is silly enough to attempt to bend a banana This is just a simple guess. Peter
(Adapted from http://www.proz.com/kudoz/English/slang/ 1044842-banana_bender.html)
According to the above text,
Alternativas
Ano: 2010 Banca: PUC - Campinas Órgão: PUC - Campinas Prova: PUC - Campinas - 2010 - PUC - Campinas - Vestibular |
Q1261918 Inglês

Instruções: Leia atentamente o texto abaixo para responder a questão.


Banana, a fruta mais consumida e perigosa do mundo


(Adaptado de Sergio Augusto, O Estado de S. Paulo, 26/04/2008)

According to the main text in Portuguese,
Alternativas
Ano: 2010 Banca: PUC - Campinas Órgão: PUC - Campinas Prova: PUC - Campinas - 2010 - PUC - Campinas - Vestibular |
Q1261906 Inglês

Instruções: Leia atentamente o texto abaixo para responder a questão.


Banana, a fruta mais consumida e perigosa do mundo


(Adaptado de Sergio Augusto, O Estado de S. Paulo, 26/04/2008)

According to the main text in Portuguese,
Alternativas
Ano: 2010 Banca: PUC - Campinas Órgão: PUC - Campinas Prova: PUC - Campinas - 2010 - PUC - Campinas - Vestibular |
Q1261904 Inglês

Instruções: Leia atentamente o texto abaixo para responder a questão.


Banana, a fruta mais consumida e perigosa do mundo


(Adaptado de Sergio Augusto, O Estado de S. Paulo, 26/04/2008)

O trecho Delícia exclusivamente tropical, a maioria dos europeus levou séculos para ver uma de perto pode ser traduzida para o inglês como:
Alternativas
Ano: 2013 Banca: UECE-CEV Órgão: UECE Prova: UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261829 Inglês
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
Considering the word shopper in the text, an example of a word with similar meaning is
Alternativas
Ano: 2013 Banca: UECE-CEV Órgão: UECE Prova: UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261828 Inglês
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
Some of Eurry Kim’s peers expect to use their abilities on
Alternativas
Ano: 2013 Banca: UECE-CEV Órgão: UECE Prova: UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261827 Inglês
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
According to the text, in terms of what is required from a student in order to apply for a master’s degree in the area of data science, one must have
Alternativas
Ano: 2013 Banca: UECE-CEV Órgão: UECE Prova: UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261826 Inglês
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
As to the way academic institutions are reacting in response to the enormous need of professionals in the field of data science, the text informs that
Alternativas
Ano: 2013 Banca: UECE-CEV Órgão: UECE Prova: UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261825 Inglês
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
According to the text, besides being referred to as a sexy job in our century, data science
Alternativas
Ano: 2013 Banca: UECE-CEV Órgão: UECE Prova: UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261824 Inglês
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
Data scientists are referred to as magicians due to the fact that, among other things, they can
Alternativas
Ano: 2013 Banca: UECE-CEV Órgão: UECE Prova: UECE-CEV - 2013 - UECE - Vestibular - Inglês - 1º Dia |
Q1261823 Inglês
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
Ethical responsibilities refer to the fact that
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Ano: 2017 Banca: UNIOESTE Órgão: UNIOESTE Prova: UNIOESTE - 2017 - UNIOESTE - Vestibular - Manhã |
Q1261545 Inglês
Are video games the next big college sport?

New kinds of competitors are joining student athletes at colleges and universities around the country. But not everyone agrees that these video game players are taking part in a sport. Sports are an established part of college life and a source of income for some schools. The football stadium at the University of Michigan in Ann Arbor, for example, holds over 107,000 people. It is one of the largest sports stadiums in the world!

Like most traditional college sports, video game competitions involve two or more teams of students officially representing their schools. Team members wear clothing with their names and school colors. They even have coaches giving them advice on how best to win.

However, there is no running or jumping or hitting other players. In fact, these new events are different from any traditional athletic activity. They are called esports, and they take place not in the real world, but in computers or other video game systems.

Professional video game competitions have been popular around the world for years. Teams and individuals compete for prize money and awards in strategic military combat games like Starcraft and one-on-one fighting games like Street Fighter. 
Fonte: adaptado de < https://app.engoo.com/daily-news/article/are-video-games-the-next-big-collegesport/xAFD2HW1EeePT98egCHuDw
Mark the CORRECT alternative, according to the text.
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Ano: 2017 Banca: UNIOESTE Órgão: UNIOESTE Prova: UNIOESTE - 2017 - UNIOESTE - Vestibular - Manhã |
Q1261544 Inglês
Are video games the next big college sport?

New kinds of competitors are joining student athletes at colleges and universities around the country. But not everyone agrees that these video game players are taking part in a sport. Sports are an established part of college life and a source of income for some schools. The football stadium at the University of Michigan in Ann Arbor, for example, holds over 107,000 people. It is one of the largest sports stadiums in the world!

Like most traditional college sports, video game competitions involve two or more teams of students officially representing their schools. Team members wear clothing with their names and school colors. They even have coaches giving them advice on how best to win.

However, there is no running or jumping or hitting other players. In fact, these new events are different from any traditional athletic activity. They are called esports, and they take place not in the real world, but in computers or other video game systems.

Professional video game competitions have been popular around the world for years. Teams and individuals compete for prize money and awards in strategic military combat games like Starcraft and one-on-one fighting games like Street Fighter. 
Fonte: adaptado de < https://app.engoo.com/daily-news/article/are-video-games-the-next-big-collegesport/xAFD2HW1EeePT98egCHuDw
De acordo com o texto, escolha a alternativa INCORRETA.
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Ano: 2017 Banca: UNIOESTE Órgão: UNIOESTE Prova: UNIOESTE - 2017 - UNIOESTE - Vestibular - Manhã |
Q1261543 Inglês
What Parents Can Do to Nurture Good Writers

Steve Graham, a professor at Arizona State University’s Teachers College, has been researching how young people learn to write for more than 30 years. He is a co-author of numerous books on writing instruction, including “Powerful Writing Strategies for All Students.”
How does reading at home help children become better writers?
is really critical, but it’s not enough. We don’t have much evidence that if you just read more, you’ll be a better writer. But analyzing text does make a difference. So when we read to kids, we can also have conversations with them about the author’s craft. How did this author make this place seem real in terms of description? What words did they use? How did they present this idea or this argument?
Should a parent correct a child’s writing, or just be encouraging?
Sometimes when kids come to you to share what they’re writing, they’re not coming for feedback. They are coming for affirmation. It’s really important we emphasize first and foremost what we really like about it. And if you’re going to give feedback, just pick one or two things. English teachers — and parents are guilty of this, too — sometimes overwhelm kids with more feedback than they can absorb all at once. The other thing that’s really important, particularly for parents, is to remember that they don’t own this piece. It’s their child’s.
What should parents look for to assess the writing instruction at their child’s school?
After about third grade, very little time is devoted to explicit writing instruction. It’s like we’ve imagined that kids have acquired what they need to know to be good writers by then! In middle and high school, the most common activities are fill-in-the-blanks on worksheets, writing single sentences, making lists or writing a paragraph summary. When you start talking about persuasive essays or an informative paper, those things occur infrequently in English class and even less so in social studies and science. So the first questions are: “Is my kid writing at school, and was he given writing assignments to work on at home? Do those require writing more extended thoughts for the purposes of analysis and interpretation?” That’s what they need to be able to do for college.
Fonte: adaptado de < https://www.nytimes.com/2017/08/02/education/edlife/parents-children-writing.html

No texto, o autor afirma que
Alternativas
Respostas
3001: E
3002: D
3003: B
3004: A
3005: C
3006: D
3007: A
3008: C
3009: E
3010: B
3011: B
3012: D
3013: C
3014: A
3015: C
3016: B
3017: D
3018: E
3019: D
3020: E