What made inland travel and trade difficult in greece?

the correct answer is "pioneers carried all of their possessions on long and dangerous trails".

the first wave of pioneers travelled in 1842. they were merely 100 people. the next year that sum climbed to 1000 men, women, and children. these people travelled around 2,000 miles to oregon in the hopes of a better life. although the first part of the trip didn't present many obstacles, as time and miles went by they learnt that threat came from simple things, like becoming ill due to unclean water or bad food.

the weather didn't much, as wagons couldn't protect them from storms. as they travelled through the desert, the intense heat caused wood to shrink. their own lips abscessed and split because of the dry air. the only cure for this was to rub axle grease on their lips.

even crossing rivers was dangerous. sometimes wheels were damaged by unseen rocks on shallow water. mud didn't much either. pioneers were afraid of indian attacks, but there aren't many records of fights between pioneers and native americans. accidents happened because of negligence, exhaustion, guns, and bad weather.

history says that 1 of 10 pioneers who travelled to oregon didn't survive the journey. diseases spread fastly because they didn't have doctors and medical care was ofently improvised. one of the most deadly diseases they came upon was cholera, which became a worldwide pandemia.

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).