Answer:
it is a function
Step-by-step explanation:
Because on the X-axis there is no numbers repeating making it a function
Answer:


So the p value is higher the significance level given 0.1, so then we can conclude that we FAIL to reject the null hypothesis that the difference mean between after and before score is equal 0. So then we don't have enough evidence to say that the score for the second exam is different than the score for the first exam.
Step-by-step explanation:
Previous concepts
A paired t-test is used to compare two population means where you have two samples in which observations in one sample can be paired with observations in the other sample. For example if we have Before-and-after observations (This problem) we can use it.
Let put some notation
x=test value before (first exam) , y = test value after (second exam)
The system of hypothesis for this case are:
Null hypothesis:
Alternative hypothesis:
The first step is calculate the difference 
The statistic given by :

The next step is calculate the degrees of freedom given by:

Now we can calculate the p value, since we have a left tailed test the p value is given by:

So the p value is higher the significance level given 0.1, so then we can conclude that we FAIL to reject the null hypothesis that the difference mean between after and before score is equal 0. So then we don't have enough evidence to say that the score for the second exam is different than the score for the first exam.
Answer:
B should have been the winner. Since B received the majority of the votes, he should be the winner, not A, and it doesnt matter how close was the election or how cmany votes A got in reality. If B had more votes for 1st place, then it should be the winner, not A. I am assuming that there were electoral fraud and someone intentionally didnt count valid votes from B.