This document presents a scatter plot comparing years of education to average weekly earnings. It shows that as years of education increases, average weekly earnings also increase. The correlation coefficient of 0.9565977261597455 indicates a very strong positive linear relationship between education and earnings. The regression model, slope, and y-intercept are provided to quantify this relationship.

1. Scatter Plot Comparison Activity Reagan Bradshaw - 2nd period

2. 11 Years (No High School Diploma) $444 12 Years (High School Diploma) $626 13 Years (Some College) $712 14 Years (Associates Degree) $767 16 Years (Bachelor's Degree) $1,038 18 Years (Master's Degree) $1,272 20 Years (Profeessional Degree) $1,610 20+ Years (Doctorate) $1,550

4. Slope: 94.13 Y intercept: -503.71 Regression Model: y=94.13x-503.71 Correlation Coefficient: 0.9565977261597455

5. Questions There is a strong relationship between the two sets of data. In most cases , the more school the person has had, the more money they are making per week. The correlation shows a strong relationship because it is very close to the number one, which is the highest number you can have. In the real world, the rate of change is telling me the relationship between the amount of education and the amount of money earned later in life. This data is extremely eye-opening, and it motivates me to do well in the future. It tells me that the harder I work, the more it will pay off.