Question

Hi I need help with this thank you! Previous question that may help answer this one : Line of best fit: ^y1=−0.02 x+4.68 ● Curve of best fit: ^y2=−0.09 x2+1.09 x+2.83 Section 2 Question 1 Using a curve to make a prediction of the y value for an x value between two existing x values in your data set is called interpolation. Suppose the year is 2005, where x = 5 years: (a) Use the equation for the line of best fit to predict the number of cell phones sold during that year. Round answers to one decimal place and be sure to include the appropriate units. Your Answer: we have the linear equation: y1=-0.02x+4.68Where x is the number of years since the year 2000, y1 ----> is the number of cell phones sold. So for the year 2005, x=2005-2000=5 years.substitute:y1=-0.02(5)+4.68y1=4.58Therefore, the answer is 4.6 cell phones sold.(b) Use the equation for the non-linear curve of best fit to predict the number of cell phones sold during that year. Round answers to one decimal place and be sure to include the appropriate units. Your Answer: We have the equation y2=-0.09x^2+1.09x+2.83For x=5 yearssubstitute:y2=-0.09(5)^2+1.09(5)+2.83y2=6.03Therefore, the answer is 6.0 cell phones sold.

Answer 1

From the information provided we will have that the predictions will be:

*Line of best fit:

`y_1=0.02(13)+4.68\Rightarrow y_1=4.94\Rightarrow y_1\approx4.9`

So, the extrapolation from the line of best fit is 4.9 sold.

*Curve of best fit:

`y_2=0.09(13)^2+1.09(13)+2.83\Rightarrow y_2=32.21\Rightarrow y_2\approx32.2`

So, the extrapolation for the curve of best fit is 32.2 sold.