When using the numbers of points scored in each Super Bowl from 1980 to the last Super Bowl at the time that this exercise was written, we obtain the following values of R2 for the different models: linear: 0.002; quadratic: 0.082; logarithmic: 0.003; exponential: 0.005; power: 0.001. Based on these results, which model is best? Is the best model a good model? Explain.

The best model is the quadratic.

Although is the best model (higher R2), its value of R2 is too low to be considered useful for analysis or prediction.

Step-by-step explanation:

The best model will be the one that has a higher R2 (goodness-of-fit). This is because the R2 coefficient reflects the how the model fit the real data. R2 will range from 0 to 1 (or 0% to 100%). A value of R2 close to 1 is almost perfect fit and a value of 0 will show no fit at all.

The "best" model (higher R2) is the quadratic model, with R2=0.082.

Although it is the higher value, it is a too low value of R2 to be consider a good model of the real data. This value of R2 shows that only 8.2% of the real data is explained by the model, and it is obviously not enough.

14

step-by-step explanation:

14 x 3 = 42

may i see the picture? it would a lot, xox