2. What was a cause for the increasing tensions of the Cold War? (1 Point)
A. Soviet expansion after WW2

B. American military build up

C. The conflict between capitalism and communism

D. All of the above

i thing that the best option is a.they feared it would cause a second economic collapse.

one of the most negatives aspects of the new deal was that it upset the balanced federal budget and led to a huge deficit for the nation while at the same time failed to end increasing unemployment. roosevelt's program, based on keynesian theories of economics, called for massive government spending to stimulate the economy. as he   failed to do this with large tax increases; large sums of money were borrowed to fund new deal programs. when the economy showed some improvement, roosevelt was concerned about inflation, and ordered cuts in government spending. unfortunately, he did so at a time when the new social security tax had cut people's disposable income. businesses were too afraid of spending, and the economy in 1937 was in worse shape than in 1929. at the end of that year, two million people were unemployed.

google has the answer

explanation:

i searched your question up and it showed me the 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).