This appears to be a regression analysis problem where you're tasked with predicting the total cost for a given production volume using least squares estimation.

The question provides a set of production volumes and associated costs, and it asks to estimate the total cost for 500 units. The task involves finding a regression equation of the form:

$\text{Total Cost} = \text{Fixed Cost} + (\text{Variable Cost per unit} \times \text{Production Volume})$

Let's break this down step-by-step:

Given Data:

• Production Volumes: 450, 500, 600, 700, 750
• Total Costs: 4943000, 5493000, 5993000, 6493000, 6993000

Solution Steps:

1. Find the Slope (Variable Cost per unit): The slope (b) in the regression equation is calculated using the least squares method. It is calculated by:

   $b = \frac{n(\sum{xy}) - (\sum{x})(\sum{y})}{n(\sum{x^2}) - (\sum{x})^2}$ where:

   • $x$ represents the production volume
   • $y$ represents the total cost
   • $n$ is the number of data points (5 in this case)

2. Find the Intercept (Fixed Cost): After calculating the slope, we can find the intercept (a) using the formula:

   $a = \frac{\sum{y} - b(\sum{x})}{n}$

3. Estimate the Total Cost for 500 units: Using the regression equation, substitute $x = 500$ to find the estimated cost.

Would you like me to perform these calculations for you?