An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume.

In the Microsoft Excel Online file below you will find a sample of production volumes and total cost data for a manufacturing operation. Conduct a regression analysis to explore the relationship between total cost and production volume and then answer the questions that follow.

Production Volume (units)	Total Cost ($)
400	4900
450	5900
550	6300
600	6800
700	7300
750	7900
Production Target	Est. Cost ($)
500

1. Compute b ₁ and b ₀ (to 1 decimal).

   b ₁ =

   b _{0 =}

   Complete the estimated regression equation (to 1 decimal).

   y = ______ + ______ x

2. According to this model, what is the change in cost (in dollars) for every unit produced (to 1 decimal)?

   _______

3. Compute the coefficient of determination (to 3 decimals). Note: report r ² between 0 and 1.

   r ² =

   What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)?

   _____ %

4. The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)?