A way to measure how well the trendline fits the data is by looking at the sum of the squared residuals.

Question

A way to measure how well the trendline fits the data is by looking at the sum of the squared residuals. When a trendline is close the points on the scatterplot, the residuals are small and so is the sum of the squared residuals. Squaring the residuals makes them positive, which removes the canceling effect of positive and negative values that may falsely imply the line is a better fit than it is. The trendline is the line that results in the smallest sum of squared residuals.

For the data in the table, find the sum of the squared residuals using the equation of the trendline: Sales = 255.95(months) + 1285.7. Round any decimals to the nearest tenth.

Months

Sinse Company Sales Predicted

Started ($) Value Residual (Residual)²

1 1,500

2 2,000

3 2,100

4 2,400

5 1,800

6 3,000

7 3,500

8 3,200

Answer 1

Dear Yuliya

My best answer at your question is attached below.

Months Sinse

Company Started Sales ($) Predicted Value Residual (Residual)2

1 1500 1541.7 41.7 1734.7

2 2000 1797.6 -202.4 40965.8

3 2100 2053.6 -46.4 2157.6

4 2400 2309.5 -90.5 8190.3

5 1800 2565.5 765.5 585913.7

6 3000 2821.4 -178.6 31898.0

7 3500 3077.4 -422.7 178633.0

8 3200 3333.3 133.3 17768.9