In which province is South Asia's administrative capital?

yellow fever and other tropical diseases

during the debate over his landmark energy policy proposal, president jimmy carter failed to consult one of the most powerful senators, louisiana’s russell long, who would have a big say over whether the legislation moved through the upper chamber. this was classic carter. with a strong distaste for congressional politics, the president simply refused to do what most other presidents would consider routine, such as courting key senators. long became so irate with the president that when he was finally invited to a white house dinner, he stood up to ask a question and, before doing so, proceeded to sarcastically introduce himself: “i’m russell long, chairman of the senate finance committee.”

this interaction is a revealing moment in stuart e. eizenstat’s fascinating new history of carter’s presidency. the former peanut farmer from georgia was a president who, according to conventional wisdom, didn’t care much for party politics; nonetheless, in eizenstat’s view, carter’s legacy on domestic and foreign policy has been vastly underappreciated. the author paints carter as a “bold and determined” leader who bravely attacked the challenges of his time. eizenstat goes so far as to argue that carter might very well be the most successful one-term president in american history.

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).