A city has been building roof-top gardens, installing heat-reflecting roofs, and creating more parks. Which of the following environmental issues is the city most likely trying to overcome?

compensation; complaints

explanation:

some employers provide "severance compensation" to employees whose employment has been terminated due to no fault of the employee

mark brainliest

the vast majority of ballots have been counted nearly two weeks after one of the biggest political upsets in modern u.s. history catapulted donald trump to the presidency.

estimates show more than 58 percent of eligible voters went to the polls during the 2016 election, nearly breaking even with the turnout rate set during the last presidential election in 2012, even as the final tallies in states like california continue to be calculated, according to statistics collected by the u.s. elections project.

but among those figures were stark contrasts in key states that swing the election to trump — in ohio, wisconsin, iowa, michigan and elsewhere — indicating the president-elect’s leap from long-shot candidate to the most powerful political position in the world may have happened in part because of apathy toward hillary clinton’s candidacy, especially among the democratic base, several political scientists and organizations monitoring voter turnout told the pbs newshour.

while clinton is leading the popular vote by more than 1.5 million over trump as of sunday, she trails president obama’s 2012 totals by more than 2 million ballots — a chasm that may have cost her the election, said david becker, co-founder of the center for election and innovation and research.

“several million voters didn’t come out to vote,” becker said. “which is telling me that this idea of the trump wave, a huge number of voters shifting over to trump, is certainly not the story.”

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).