It has a positive correlation because the points all trend upward. In other words, as the independent variable on the x-axis increases, the dependent variable on the y-axis also increases. Therefore, the line of best fit that is drawn through the data represents a positive line as it has a positive slope. This verifies that our data has a positive correlation.

I. is a true statement about the scatter plot: as quality increases, price tends to increase.

II. is not true - the points under the line have a relatively low price compared to their quality.

III. is also not true - the points above the line have relatively low quality compared to their price.

To answer this question correctly, we need to recall what "outlier" means. An outlier is a value that is much smaller or larger than the rest of the values in a set of data. Also, a data point that does follow the same pattern as the rest of the set could be described as an outlier. In this case, if we had a student that studied  hours, but received a test score of  that data point would be considered an outlier because it doesn't follow the same pattern as the rest of the set. However, there are no data points in this set that don't follow the pattern; thus, there are no outliers in this set. 

In the provided scatter plot, we can pick out data points and organize them from least to greatest, based on hours spent studying:

Based on the results, we can see that as the number of hours spent studying increased, the test grade also increased; thus, a positive association, a higher number of hours spent studying correlated to a higher test score.

To answer this question correctly, we need to recall what "outlier" means. An outlier is a value that is much smaller or larger than the rest of the values in a set of data. Also, a data point that does follow the same pattern as the rest of the set could be described as an outlier. In this case, if we had a student that had  missing assignments, but received a test score of  that data point would be considered an outlier because it doesn't follow the same pattern as the rest of the set. However, there are no data points in this set that don't follow the pattern; thus, there are no outliers in this set. 

To answer this question correctly, we need to recall what "outlier" means. An outlier is a value that is much smaller or larger than the rest of the values in a set of data. Also, a data point that does not follow the same pattern as the rest of the set could be described as an outlier. 

Let's look at our answer choices:

This point is showing that a student who studied for  hours received a  on the test. If we look at our graph, we can see that the two students that spent  hours studying received scores of  and . A score of  fits in with that data; thus,  is not an outlier. 

This point is showing that a student who studied for  hour received a  on the test. If we look at our graph, we can see that the two students that spent  hour studying received scores of  and . A score of  fits in with that data; thus,  is not an outlier. 

This point is showing that a student who studied for  hours received a  on the test. If we look at our graph, we can see that the two students that spent  hours studying received scores of  and . A score of  fits in with that data; thus,  is not an outlier. 

This point is showing that a student who studied for  hours received a  on the test. If we look at our graph, we can see that the student who spent  hours studying received a score of . Also, if we look at the student who studied for  hours, that student received an . Based on this results,   would be an outlier. 

To answer this question correctly, we need to recall what "outlier" means. An outlier is a value that is much smaller or larger than the rest of the values in a set of data. Also, a data point that does not follow the same pattern as the rest of the set could be described as an outlier. 

Let's look at our answer choices:

This point is showing that a student had   missing assignments received a  on the test. If we look at our graph, we can see that the student that had  missing assignments received a score of  . A score of  fits in with that data; thus,  is not an outlier. 

This point is showing that a student who had  missing assignments received an  on the test. If we look at our graph, we can see that the student that had  missing assignments received score of . A score of  fits in with that data; thus,  is not an outlier. 

This point is showing that a student who had   missing assignments received a  on the test. If we look at our graph, we can see that the two students that had  missing assignments received scores of  and . A score of  fits in with that data; thus,  is not an outlier. 

This point is showing that a student who had  assignments missing received a  on the test. If we look at our graph, we can see that the student who had  missing assignments received a score of . Also, if we look at the student who had  missing assignments, that student received a . Based on this results,   would be an outlier. 

To answer this question correctly, we need to recall what "outlier" means. An outlier is a value that is much smaller or larger than the rest of the values in a set of data. Also, a data point that does not follow the same pattern as the rest of the set could be described as an outlier.

In this case, we are looking for a number that doesn't match with the other numbers provided in a set:

 has a much larger value than the other number in the set; thus,  is an outlier. 

To answer this question correctly, we need to recall what "outlier" means. An outlier is a value that is much smaller or larger than the rest of the values in a set of data. Also, a data point that does not follow the same pattern as the rest of the set could be described as an outlier.

In this case, we are looking for a number that doesn't match with the other numbers provided in a set:

 has a much larger value than the other number in the set; thus,  is an outlier. 

To answer this question correctly, we need to recall what "outlier" means. An outlier is a value that is much smaller or larger than the rest of the values in a set of data. Also, a data point that does not follow the same pattern as the rest of the set could be described as an outlier.

In this case, we are looking for a number that doesn't match with the other numbers provided in a set:

 has a much smaller value than the other number in the set; thus,  is an outlier.