As the nation expanded, where did War Hawks want land?

by 1890, the united states had by far the world's most productive economy. american industry produced twice as much as its closest competitor--britain. but the united states was not a great military or diplomatic power. its army numbered less than 30,000 troops, and its navy had only about 10,000 seamen. britain's army was five times the size of its american counterpart, and its navy was ten times bigger. the united states' military was small because the country was situated between two large oceans and was surrounded by weak or friendly nations. it faced no serious military threats and had little interest in asserting military power overseas.

alliances in ww1 were different from ww2 because the entente in ww1 made up of serbia,russia,france,britan,japan and italy later america  and all allied in a sort of balance of power and too keep germany,austria-hungary,and the ottomans down. russia allied the serbians in order to exert its influence in the balkans while france allied the russians because france was still in dismay and insulted after the defeat to the germans during the unification of germany and britian allied the belgians after the germans invasion of belgium.in ww2 the alliances were in a preemptive attempt to deter any further wars into happening while germany and italy allied since they were insulted and humiliated after the previous war while also sharing a similar ideology of facsim along with japan which all 3 had a want for world domination and agreed to assist one another in the endevours 

explanation:

the democratic and republican parties

explanation:

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).