1. The equation of a line is y = mx + b, where m is the slope and b is the y-intercept. Therefore, the y-intercept is 25, and it represents the cost for insurance
2. The slope is m = 20, and it represents the monthly fee. (50 is the y-intercept.)
3. If the scatter plot's points loosely scattered going down to the right, this is a negative slope, and thus it is a negative correlation.
4. We would expect the data to be negatively correlated, since the longer a person has been jogging, the more tired he would be.
5. Plot all data together on a dot plot to assess if there is any visible correlation between the data sets. (The second step would be finding the correlation coefficient. Sometimes, a visual look already tells you whether or not there is a correlation. When uncertain, that's when the correlation coefficient must be calculated).
6. No; even though there is a strong positive correlation, playing violin doesn't cause students to get better grades. It may be that students who already have good grades decide to learn something new, so the learn to play the violin.
7. This is a causation, because a refrigerator keeps things cold. It is not just a correlation, but there is theoretical reason to expect the result.