The political cartoon below was drawn by thomas nast in 1871: a political cartoon shows a heavy set man with a long nose and a beard in a suit and vest. he is smoking a cigar and has a menacing expression. he leans against a large box that says, in counting there is strength. on top of that box is a smaller container labeled, the ballot. dialogue under the cartoon reads, thats whats the matter. boss tweed, as long as i count the votes, what are you going to do about it? say? public domain what issue does this cartoon address?

so, based on the research i've done. the u.s. government were always on a wild goose chase just to take down castro. he then retired his trone to his brother raul in 2008 due to some health issues. so it's obvious your answer would be:

castro had no allies from which he could receive aid.

hope this and have a fantastic day!

                                                    -wolfiewolffromsketch

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).

because he is a great ruler