Which of these is true about pre colombian north and south america a. they were united by a single government, b. they were dependent on overseas trade, c. they had complex societies, d. they created a language understood by all groups

both eastern and western early north american cultures were known for building wigwams and longhouses.

wigwams, also called wetus, were small houses of 8-10 feet tall, made of wooden frames covered with woven mats and sheets that were used by algonquian indians. similarly,   longhouses were also used by algonquian and the iroquois tribes, and they were built as well with pole frames and elm bark covering. however, the main difference between wigwams and longhouses is that the latter was much larger than the former, with 200 feet long, 20 feet wide, and 20 feet high with inner raised platforms used for sleeping space.

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).