"Winter is such a cool time to see the stars twinkle" can you write a paragraph on what The author's purpose, or reason, was for writing this text. Explain whether they were successful in this achieving this purpose. You supporting details and write in (THRID PERSON)

"a government in which power is divided between state and national levels". federalism is a system of government in which entities such and state and province, share power with the national government.

1. the townshend acts of 1767 “threaten the country with poverty and ruin.”

at a town meeting held at faneuil hall in boston on october 28, 1767, boston freeholders and residents discussed the implications of the brutal townshend acts levied against the colonists. the townshend acts were a set of four acts passed by the british parliament in the summer of 1767 in order to generate revenue for the crown (through duties on goods such as lead, glass, paper, and tea) as well as exert british control over the increasingly rebellious colonists.

during the oct. 28 meeting, the bostonians found:

the excessive use of foreign superfluities is the chief cause of the present distressed state of this town, as it is thereby drained of its money: which misfortune is likely to be increased by means of the late additional burthens and impositions on the trade of the province, which threaten the country with poverty and ruin.

as a result, the citizens unanimously voted to boycott all british-made goods.

a hypothesis is an expected answer to a question, usually based on some theory or prior research. hypothesis testing is a method of determining the viability of a hypothesis. let’s use the us presidential election as an example. there are many hypotheses (questions) about how people feel or whom they will vote for. the only way to know the 100% “truth” about the answers to these questions is to ask every single possible voter – something that is impossible, expensive, time consuming etc. instead, we take samples and use statistics to make “best guesses” about the answer to a particular hypothesis. we never know for sure if our conclusion is right at the time we accept/reject it, but these techniques, when used appropriately can get us close to the truth most of the time (which is a lot better than guessing, flipping coins or throwing darts to get answers).

the tricky part about hypothesis testing is that we have to think somewhat backwards about it – we have to test what is known as the “null hypothesis”. as an example, the hypothesis might be “obama is more popular than romney” while the null hypothesis is “there is no difference in popularity between obama and romney”. we focus on the null hypothesis because it tells us exactly what the expected value of our tests should be (obama popularity = romney popularity) and we can collect data and see if it comes out that way (see next section on “significance”). if it does, then we “accept the null hypothesis” and reject our original hypothesis. if the null hypothesis is disproven, we look at the data to see if our original hypothesis holds (obama> romney).