Determine whether the graphs of the given equations are parallel, perpendicular, or neither. Explain. y=x+11
y=-x+2

the exact role and status of women in the roman world, and indeed in most ancient societies, has often been obscured by the biases of both ancient male writers and 19-20th century ce male scholars, a situation only relatively recently redressed by modern scholarship which has sought to more objectively assess women's status, rights, duties, representation in the arts, and daily lives; and all this from almost exclusively male source material dealing with a male-dominated roman world.

women in mythology

unlike some other ancient cultures such as the greeks who had formed a creation myth where woman was a creature secondary to man and, more specifically, in the form of pandora, a bringer of unhappiness and vices, the romans had a more neutral approach where humanity, and not specifically the male, was created by the gods from earth and water. ovid's metamorphoses, for example, does not specify whether the first human was a man or a woman. at least in a physical sense then men and women were not regarded as belonging to a different species as in the greek world, a view often reiterated in roman medical treatises.

they had a lot of depression during the revolutionary war

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).