Question

2. The following are two hypothetical statements by American politicians. Politician A: "Our economy is in the crapper! Thirty states had falling incomes last year." Politician B: "Our economy is showing appreciable gains: Seventy percent of Americans had rising incomes last year." a) Suppose both statements are true. How to reconcile these two seemingly contradicting statements? (4 points) b) What lessons can we learn about descriptive statistics from this example? (4 points)

Answer 1

a)

In the given questions the reasons why both politicians my be is due to Fiscal deficit that various governments run.

- Fiscal deficits are negative adjusts that emerge at whatever point a government goes through more cash than it gets during the fiscal year.

- A government encounters a fiscal deficit when it goes through more cash than it takes in from charges and different incomes barring obligation over some timeframe.

- This hole among salary and spending is along these lines shut by government getting, expanding the national obligation.

- This awkwardness, now and then called the current records deficit or the spending deficit, is normal among contemporary governments everywhere throughout the world.

- Since 1970, the U.S. government has had higher uses than incomes for everything except four years. With ongoing years every year indicating a fiscal deficit in the U.S. of more than $1 trillion.1

- An expansion in the fiscal deficit, in principle, can support a languid economy by giving more cash to individuals who would then be able to purchase and contribute more.

- Long haul deficits, be that as it may, can be unfavorable for financial development and strength.

- The U.S. has reliably run deficits over the previous decade.

b)

- Descriptive statistics principles deals with when we can used the properties of the data to analyse it . There are 4 different kind of descriptive statistics. I this particular case we can use the concepts of Descriptive statistics of Dispersion. This concept of variation allows us to use when data is so wide and spread and we can understand how so wide spread data affects mean.