A researcher fits a quadratic regression model $\hat{y}=2+0.5x-0.1x^2$ to the following data:

What is the sum of squares of residuals for this model?

An analyst is modeling the number of goals scored in each annual hockey final since $2010$ (coded as $1$, $2$, $3$,...). The $R^2$ values for different models are:

linear: $0.005$

quadratic: $0.011$

logarithmic: $0.002$

exponential: $0.009$

power: $0.004$.

Which model is the best according to $R^2$? Does it have a good predictive power?

Which choice best distinguishes quadratic regression from linear regression when examining a scatterplot?

Given the quadratic regression output a = -0.5, b = 4, c = 1, determine the parabola's concavity and compute the vertex coordinates (x_v, y_v).

Which of the following describes the correct TI-84 steps to run a quadratic regression and automatically store the resulting equation in Y1 for graphing?