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People are getting sick. in the first week, three people are sick. the second week there are 7. 3rd week there are 18 people sick. 4th week there are 43 cases of people sick.

Here is a chart in case it doesn't make sense...

week .....sick cases

1............... 3

2 ...............7

3............... 18

4 ...............43

How many people would you predict to be sick in the next few weeks?

can you come up with a rule to describe the number of people sick on any given week?

when did people start getting sick?

What are the limits to your rule?

explain how you solved the problem.

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Chika Ilonah
Chika IlonahLv10
28 Sep 2019

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Related questions

Unemployment and its types, and the Natural Rate of Unemployment.

1) Frictional unemployment is the result of

A) an economic recession.

B) the economic decline of major industries.

C) the normal process of jobs being created and destroyed.

D) people not getting along (having friction) with their employers.

E) changing weather throughout the year.

2) Bill has graduated with his degree in economics. Through Career Services he submitted his resume to several companies and he will visit them during the next two weeks. Bill is considered

A) not in the labor force.

B) frictionally unemployed.

C) structurally unemployed.

D) cyclically unemployed.

E) employed because he is visiting firms.

3) Structural unemployment includes people who become unemployed from

A) changes in the seasons.

B) normal changes in the labor force.

C) technological changes.

D) changes in the business cycle.

E) going back to school.

4) An employee who is fired from his or her job because he or she lacks the skills required to accomplish the task, is part of ________ unemployment.

A) frictional

B) cyclical

C) unskilled

D) structural

E) withdrawal

 

5) How would you best describe a manufacturing employee who has been fired because he was replaced by a robot (new technology) and does not have the skills necessary to help operate the robot?

A) job leaver

B) entrant/reentrant

C) cyclically unemployed

D) structurally unemployed

E) withdrawal

6) Seasonal unemployment includes people who become unemployed from

A) the seasonal weather patterns.

B) normal changes in the labor force.

C) technological changes.

D) changes in the business cycle.

E) changes in international competition.

7) Cyclical unemployment includes people who become unemployed from

A) changes in the seasons.

B) changes in international competition.

C) technological changes.

D) changes in the business cycle.

E) normal labor market turnover.

 

8) The type of unemployment that arises from a decrease in real GDP is called

A) frictional unemployment.

B) structural unemployment.

C) seasonal unemployment.

D) cyclical unemployment.

E) downturn unemployment.

9) John has been laid off from his job because of a general downturn in the economy. John's unemployment is best classified as

A) cyclical.

B) seasonal.

C) structural.

D) frictional.

E) avoidable.

 

 

10) Full employment means that

A) 100 percent of the labor force have jobs.

B) only those who are willing, able and looking for work are unemployed.

C) the cyclical unemployment rate is zero.

D) the natural unemployment rate is zero.

E) the frictional unemployment rate is zero.

 

11) The natural unemployment rate is the unemployment rate that exists when there is no

A) structural unemployment.

B) frictional unemployment.

C) cyclical unemployment.

D) cyclical or structural unemployment.

E) seasonal unemployment.

12) The natural unemployment rate equals the sum of

A) cyclical and frictional unemployment.

B) cyclical, seasonal, and structural unemployment.

C) frictional, seasonal, and structural unemployment.

D) seasonal and cyclical unemployment.

E) cyclical, frictional, seasonal, and structural unemployment.

 

What do you believe is the ultimate impact of technology on job creation? Should there be curbs to the pace of modernization?

(Answer in a paragraph(around 200 words))

What Econ 101 Can Teach Us About Artificial Intelligence

Here's why advancing technology often leads to more jobs for humans, not fewer

A Tesla Model X 75D semi-autonomous electric vehicle is parked at the Governor's Mansion in Olympia, Wash., this year. Goldman Sachs predicts that 25 years from now, driver employment will be growing by 300,000 less per year because of autonomous vehicles.

By Greg Ip

Aug 9, 2017

The first chart you draw in Economics 101 is the downward-sloping demand curve. It shows that when the price of something drops, people consume more of it.

This elementary rule of economics is remarkably helpful in discussing the effects of technological change. As I wrote last week, when technology makes something cheaper, we consume more of it, often by finding new uses. This lesson repeats through history: When coal-fueled steam power became more efficient in the 1800s, demand for steam power and coal spread. When automated teller machines made it cheaper to operate bank branches in the 1980s, banks opened more branches.

My column cites spreadsheet programs like Lotus 1-2-3, whose arrival in the early 1980s made repetitive recalculation vastly simpler and faster. This reduced demand for bookkeepers but created more demand for people who could run numbers in new and interesting ways, such as accountants and management consultants.

In a recent article for the Harvard Business Review, Ajay Agrawal, Joshua Gans and Avi Goldfarb, economists at the University of Toronto who study artificial intelligence, say that in the 1990s, economists didn’t buy into the hype that the internet and the World Wide Web would upend everything:

“It wasn’t that we didn’t recognize that something changed. It was that we recognized that the old economics lens remained useful for looking at the changes taking place. The economics of the ‘New Economy’ could be described at a high level: Digital technology would cause a reduction in the cost of search and communication. This would lead to more search, more communication, and more activities that go together with search and communication. That’s essentially what happened.”

They apply that lesson to artificial intelligence and more specifically to machine learning, the use of powerful algorithms to make predictions from patterns in large quantities of data. Machine learning, they say, means many problems will be reframed as prediction problems. Autonomous driving no longer involves programming the car to respond in a certain way to a variety of controlled scenarios, but instead, to watch what humans actually do and then respond the same way.

How does this affect jobs? The authors says it depends on whether the technology competes with or complements what you do. Spreadsheets competed with what bookkeepers do (record keeping and calculation) and thus made them less valuable, but complemented what accountants and consultants do (analysis), and made them more valuable.

Mssrs. Agrawal, Gans and Goldfarb say that AI reduces the value of those who predict things for a living, such as whether a mark on an X-ray is a tumor, but it raises the value of those who use predictions to make judgments:

“When prediction is cheap, diagnosis will be more frequent and convenient, and thus we’ll detect many more early-stage, treatable conditions. This will mean more decisions will be made about

medical treatment, which means greater demand for the application of ethics, and for emotional support, which are provided by humans.”

So AI will create winners and losers within and among industries and occupations. But what will the net effect be? More jobs or less, and for whom? This isn’t knowable, but history suggests that while a specific occupation or industry may suffer losses, the aggregate effects will be positive. The growth in accounting and analytical jobs since the early 1980s is much larger than the loss of bookkeeping jobs.

Nor did all those bookkeepers necessarily lose jobs; many probably became accountants or analysts. As Mr. Gans told me, bookkeepers may have been best placed to exploit the capabilities of spreadsheets: “If you were doing calculations all day as a bookkeeper, chances are you thought a bit about why you are doing that. When you got a spreadsheet, rather than doing one calculation per day you could do 10 to 50, so you had a better sense of what the [calculations] might say.”

Some readers said AI is a much bigger threat than spreadsheets because it has so many more potential applications—and they displace uniquely human abilities. I agree with the first part, less so with the second. I suspect workers in previous eras, whether they drove a horse and plow, handled a stock trade or connected a phone call, thought there was something about their job that a machine could never replace.

Will the disruptions this time around be greater? Maybe, but not necessarily. Goldman Sachs predicts that 25 years from now, driver employment will be growing by 300,000 less per year because of autonomous vehicles. That’s 25,000 jobs per month to make up, compared with the 5,000 per month that the decline in bookkeeping since 1985 represents. But it’s hardly insurmountable in a labor market where five million jobs are created and destroyed each month.

Others said I was ignoring the potential for rogue algorithms and robots to turn on us or strip us of our freedom.

The experts, of which I am not one, tell me AI is nowhere near that capability. (Before the robots can kill us they must first stop killing themselves.) And don’t assume spreadsheets have been all benign. Excel may not have slain anyone Terminator-style, but it did help wound J.P. Morgan through its role in the “London Whale” trading disaster.

Which brings me to the final point. We should not confuse what technology enables us to do with how much better off it makes us. Spreadsheets enabled analysts to construct much more intricate forecasts of stock prices and the economy, but didn’t make those forecasts any more accurate. AI may enable companies to better manage the risks of their products and actions, but those products and actions may not be more profitable. Many a CEO has wondered whether the money they spend on spreadsheet-wielding consultants yields any real value. Some day they may wonder the same thing about their AI-wielding consultants.

Read the articles and consider two people, Mon and Shaman, that can produce 2 goods, shrimp and mobile apps.

If Mon and Shaman devoted themselves to shrimp and mobile app production, the chart below shows how much each person can produce per hour.

Complete the first table by showing how many shrimp and mobile apps each person would produce if they did not specialize.

Hours worked per year

 Total amount produced if each person devotes all their working hours per year to each good.

Shrimp per hour

Mobile Apps per hour

Total Shrimp

Total Mobile Apps

Mon

3500

50

1

Shaman

2000

10

5

In a world hungry for cheap shrimp, migrants labor overtime in Thai sheds

By Jason Motlagh, Published: September 19, 2012

Jason Motlagh/For The Washington Post - Burmese migrant workers peel shrimp at a processing factory in Samut Sakhon province in Thailand. High standards allow the factory to export its seafood to the United States.

MAHACHAI, Thailand — At an age when she should have been in a classroom, Thazin Mon discovered her knack for peeling shrimp. To help support her Burmese migrant family, the 14-year-old pulled 16-hour shifts, seven days a week, for less than $3 a day. “I am uneducated, so I work. I have to work bravely,” she says.

Although she was the best peeler in the factory, speed was never enough. Mon was beaten if she slowed down, she said, and when she asked for a day off to rest hands swollen with infection, her boss kicked her and threatened rape.

Thanks to a bottomless appetite for cheap shrimp in the West, Burmese migrants such as Mon are the backbone of a Thai shrimp industry that is the world’s third largest. The United States is Thailand’s top customer, accounting for a third of the country’s annual shrimp exports.

Rights groups say that overseas demand for shrimp products in greater volume has fueled a culture of exploitation in the Thai industry. They insist that the failure of foreign companies to sufficiently verify the origin of the shrimp they import allows abuses to persist.

“If you look at the cost of shrimp overseas, it’s very, very cheap, and that comes from the exploitation inherent in the shrimp industry,” says Andy Hall, an expert on migration at Mahidol University who tracks Burmese labor in the Thai seafood industry.

Brisk business with major U.S. retailers such as Wal-Mart, Costco, Sam’s Club and Red Lobster pumps more than $1 billion in revenue each year into the Thai economy, the second largest in Southeast Asia. As Thai living standards have risen, a shortage of unskilled labor has attracted tens of thousands of Burmese migrants looking to escape the poverty and job scarcity that has gripped their homeland for decades.

Most head to Samut Sakhon province, the heart of the processing industry just south of the capital, Bangkok, where modern facilities line the highway alongside fast-food chains and car dealerships. The more prominent factories are the size of football fields, with neon signage and billboards that feature smiling children. But there’s a darker side behind the scenes, activists say.

Of an estimated 400,000 migrants at work in the province, only about 70,000 are legally registered. The rest are employed illegally in anonymous peeling sheds that supply the larger companies that must fill massive orders from abroad. At this lower end of the supply chain, according to migrant activists, crooked brokers and employers trap scores of Burmese in abusive conditions tantamount to slavery, particularly in the shrimp industry.

“The small factory owners know that most of their workers are undocumented, so they can control the workforce however they want — such as locking workers in until they finish their work,” says Sompong Sakaew, a labor activist based in Mahachai, the provincial capital. “There are also teenagers between 12 and 17 years old in the workforce.”

Sold into waking nightmare

Problems for Burmese migrants typically start as soon as they link up with brokers who promise steady work and a decent salary, only to sell them into a nearly inescapable cycle of debt bondage.

Min Oo, 28, a Burmese farmer who lost his home in a flood, said he paid a broker the equivalent of $500 to smuggle him across the border to Samut Sakhon, with the guarantee of a minimum-wage (about $10 a day) factory job. Instead, he said, the broker sold him into a waking nightmare, with 18-hour workdays in a shrimp-processing factory and net earnings of no more than $20 a week, leaving almost nothing to send home.

In some cases, migrant workers and rights groups allege, police officials or their relatives hold an ownership stake in unregistered peeling sheds. More commonly, the critics say, the authorities or those they protect shake down undocumented workers for bribes to supplement their incomes, knowing that the migrants would rather pay up on the spot than be deported to Burma.

Despite occasional police action and robust anti-trafficking laws, Sakaew, the labor activist, estimates that fully a quarter of the 1,200 to 1,300 factories in Samut Sakhon province are unregistered and, therefore, ripe for abuse. With so much profit-induced apathy on the Thai side, activists say reform pressure must come from Western companies whose trade partnerships drive the shrimp industry.

Codes of conduct

It is difficult to establish precise links between the larger Thai companies that process shrimp of dubious origin and the Western companies whose consumers increasingly demand ethical sourcing.

To do business overseas, Thai companies must qualify for membership in the Thai Frozen Foods Association, which adheres to globally recognized codes of conduct and carries out unscheduled inspections. Spokesman Arthon Piboonthanapatana asserts that anyone found guilty of labor -abuses would be expelled. In more than three years of inspections, he said, this has never happened.

“If the shrimp is from TFFA members, I can 100 percent guarantee” that it is produced without labor exploitation, he said.

But critics say that until the Thai shrimp industry requires larger factories to provide records of lower-level suppliers and follows through with random inspections, the shrimp it exports will remain tainted by human trafficking and labor abuses.

For the past three years, the State Department has given Thailand a poor grade on human trafficking, citing it among countries that do not fully comply with the minimum standards for efforts to combat the problem.

After the release of the department’s report in 2012, Thai Foreign Minister Surapong Tovichakchaikul said his country would improve its performance by strengthening cooperation among agencies tasked with fighting human trafficking.

Motlagh reported with a grant from the Pulitzer Center on Crisis Reporting.

More world news coverage: - Turmoil in Egypt stalls talks on U.S. aid - Suicide blast kills 12 near Afghan capital’s international airport - U.S. troops to cut missions with Afghan forces - Read more headlines from around the world.

Google reportedly acquiring Waze app for $1.3 billion

News ends months of rumors on deals with Apple, Facebook, or Google, according to Globes; Waze source refuses to comment

By David Shamah June 9, 2013, 7:20 pm

Waze co-founder Uri Levine at a Jerusalem conference in May (photo credit: Flash90)

After dating at least three of the biggest tech companies in the world, it appeared Sunday night that Waze was finally getting the ring — one worth $1.3 billion, according to a report in the Israeli business newspaper Globes.

That’s the sum Google has reportedly agreed to pay for Waze, the Ra’anana-based crowdsourced driving and navigation app with 50 million users around the world. The figure is $300 million higher than Facebook reportedly offered to pay for the firm earlier this year.

A company source contacted by The Times of Israel had no comment on whether talks with Google (or any other party) were on or off. “We don’t comment on rumors and speculation in general,” the source said.

The purchase, reported by Globes citing an anonymous source, would be the biggest buyout yet for an Israeli consumer firm, far outstripping Face.com’s $60-million sale to Facebook last year. Indeed, it is believed that it would be the biggest sum paid for any app, ever.

In May, it was rumored that Facebook had offered nearly $1 billion for Waze, but negotiations broke down several weeks later, apparently over Facebook’s insistence that Waze move its R&D from Israel to one of Facebook’s existing facilities, in the US or Britain. Several weeks later, it was reported that Google was interested in Waze, and that the search giant had offered as much as $1 billion for the company as well.

Previous rumors — earlier this year — had Apple as a prospective Waze buyer, with an offer of $400 million for the Israeli company.

A Google-Waze deal would likely not get snagged over location; Google already has several large R&D facilities in Israel, and employs hundreds of engineers here. Integrating the already existing Waze group into the Google infrastructure would be much simpler than getting Waze integrated with Facebook, local social media expert Yotam Tavor told The Times of Israel.

However, it appears that location wasn’t the only issue. As recently as several weeks ago — amid the rumors that Google was poised to make an offer for Waze — company insiders were quoted in news reports as saying that members of the Waze board of directors believed that they would be selling themselves short if they “settled” for $1 billion — and that they could raise much more with an IPO. How much Waze would fetch in an IPO isn’t clear, but if the latest report is true, Google apparently agrees with the Waze officials opposed to a sale.

Google already has its own mapping and driving app, and competes with Waze, but the latter dominates in most of the markets where Google’s Navigator app is used. As such, Google and Waze are competing in the same space, but most users agree that the Waze app is much more elegant and user-friendly than the Google one.

In addition, Waze has built an active and loyal social network, which is highly engaged with the app, as well as a built-in mobile ad platform. In its latest version, it supplies Google Maps-like recommendations — making it a perfect match for Google, Tavor said.

,

Information

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Information text

The Outcome Without Trade

The Outcome With Trade

The Gains From Trade

What they Produce and Consume if they do not specialize according to comparative advantage.

What They Produce if they fully specialize in one good.

What They Trade

What They Consume

The Increase in Consumption

Mon

1.)

Point A

5.)

9.)

10.)

13.)

Point A*

17.)

A to A*

2.)

6.)

14.)

18.)

Shaman

3.)

Point B

7.)

11.)

12.)

15.)

Point B*

19.)

B to B*

4.)

8.)

16.)

20.)

Suppose Mon and Shaman do not specialize according to comparative advantage and exchange but instead choose to be self-sufficient.

Further, they devote half of their hours in each year to each good and they consume everything they produce domestically.

After specialization according to comparative advantage, they exchange 5,000 apps for 75,000 shrimp.

Compute values for the numbered cells.

Question 29

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What is the opportunity cost of producing shrimp for Mon?

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Question 30

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What is the opportunity cost of producing shrimp for Shaman?

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What is the opportunity cost of producing Mobile Apps for Mon?

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What is the opportunity cost of producing Mobile Apps for Shaman?

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1.) Before specialization, how much shrimp will Mon produce?

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2.) Before specialization, how many mobile apps will Mon produce?

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3.) Before specialization, how much shrimp will Shaman produce?

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4.) Before specialization, how many mobile apps will Shaman produce?

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5.) If they specialize according to comparative advantage, how much shrimp will Mon produce?

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6.) If they specialize according to comparative advantage, how many mobile apps will Mon produce?

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7.) If they specialize according to comparative advantage, how much shrimp will Shaman produce?

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8.) If they specialize according to comparative advantage, how many mobile apps will Shaman produce?

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9.) After specialization according to comparative advantage, they exchange 5,000 apps for 75,000 shrimp, i.e. each country sells some of the good in which they have a comparative advantage for the good in which they have a comparative disadvantage.

How much shrimp will Mon trade?

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10.) How many mobile apps will Mon trade?

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11.) How much shrimp will Shaman trade?

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12.) How many mobile apps will Shaman trade?

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13.) After trade, how much shrimp will Mon consume?

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14.) After trade, how many mobile apps will Mon consume?

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15.) After trade, how much shrimp will Shaman consume?

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16.) After trade, how many mobile apps will Shaman consume?

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17.) After trade, Mon’s shrimp consumption increased by how much?

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Question 50

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18.) After trade, Mon’s mobile app consumption increased by how much?

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Question 51

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19.) After trade, Shaman’s shrimp consumption increased by how much?

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20.) After trade, Shaman’s mobile consumption increased by how much?

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Question 53

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What is the total amount of shrimp produced if Mon fully specializes in shrimp production?

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Question 54

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What is the total amount of shrimp produced if Shaman fully specializes in shrimp production?

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Question 55

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How many mobile apps will Mon produce if she fully specializes in producing mobile apps?

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Question 56

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How many mobile apps will Shaman produce if he fully specializes in producing mobile apps?

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