“the economic decline [of kush] may have been hastened by overgrazing of the land and by the progressive desiccation of the butana. but the most serious threat came from axum, a kingdom that rose to power in the highlands of ethiopia to the southeast. . axum challenged kush’s monopoly of trade in the african interior. the two inevitably clashed, and axumites, on the offensive, carried the battles into the butana. but by the time the axumite king aezanas marched into kush around a. d. 350, its monarchy apparently no longer existed. a detailed axumite inscription makes no mention of the meroites, but does refer to the noba, a people who were known to have harrassed the meroites from the west bank of the nile. so the final downfall of the kingdom of kush is veiled in almost complete darkness.” —william y. adams, archaeologist, as quoted in splendors of the past: lost cities of the ancient world the causes of the final downfall of kush are a. well known. c. mysterious. b. detailed. d. unusual.

answer: (fluidity)is the correct answer.

explanation: because of this characteristic, success on the battlefield depends in large part on the ability to adapt to proactively change events to our advantage as well as to react quickly to constantly changing conditions

answer:   the name of this act is known as the:

    " american recovery and reinvestment act of 2009 " .

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).