The data set shows the number of practice passes a quarterback successfully completed preparing for a competition and the number of passes the quarter throw during a timed competition. (photo 1) use technology to find the equation and coefficient of determination for each type of regression model. use the number of practice passes for the input variable and the number of competition passes for the output variable. (photo 2) which model best fits the data set?

The model that best fits the data is the one with the highest value of . In this case it is the quadratic, with a coefficient of determination .

Step-by-step explanation:

To find the different regression models, the Excel software was used.

For the linear regression model, the following equation was obtained:

with a coefficient of determination

For the quadratic regression model, the following equation was obtained:

with a coefficient of determination

Finally, for the exponential regression model, the following equation was obtained:

with a coefficient of determination

The coefficient of determination measures how well a predictive mathematical model fits reality. The value of is always between 0 and 1. The closer you get to 1, the more accurate is the built model.

Therefore, the model that best fits the data is the one with the highest value of . In this case it is the quadratic, with a coefficient of determination

The results obtained are summarized in the attached table.

only 10/60 isn't equivalent

hope this : )

a

step-by-step explanation: