Who was the first Egyptian pharaoh

when studying cause and effect, historians usually group the causes into different categories. for example, cultural causes reflect how a society’s literature and art convey the way the society saw itself in relation to the rest of the world. another resource that historians use to understand society is pop culture, which tells them the trends and ideas that are preferred by the common people. when studying cause and effect, it’s important to remember multiple causation, or the idea that an effect could have several causes and vice versa.  

the correct option is “cultural causes” since art and literature are related to the culture of a place. culture is determined by literature, art, music.

the correct option is “pop culture” since it reflects the likes and ideas of common people whereas the rest of the options do not focus on common people.  

the correct option is “multiple causation” since it refers to the idea that events are caused by multiple reasons, not just a single one.  

i believe it's that they cared for people. hope this ! : )

i believe that d is the right answer

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).