TVA describe the impact that the program had on trying to end the Great Depression or help those suffering from it.

One of the most famous and successful projects begun by the federal government during the Great Depression was the Tennessee Valley Authority, or TVA. The TVA aimed to help reduce these problems by teaching better farming methods, replanting trees, and building dams. As for flood control, the TVA has flooded an estimated 730,000 acres—more land than the entire state of Rhode Island. Most directly affected by TVA flooding were the thousands of people forced out of their homes. The TVA spent $15 billion building nine nuclear power plants—and none of them worked.  The unemployment rate in 1940 was still at a depression level of about 15 percent. By contrast, liberal economists today often claim that the reason the recovery struggled so long was that the government did not go far enough. When the United States entered the war in 1941, it finally eliminated the last effects from the Great Depression and brought the U.S. unemployment rate down below 10%. In the US, massive war spending doubled economic growth rates, either masking the effects of the Depression or essentially ending the Depression.

Explanation:

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mutation is when you body morphs to something odd or bad looking (no offense)

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).