Cost Estimates Regression MCQ

Regression analysis for cost estimation is a high-yield CPA and CMA exam topic, and this worked multiple-choice question walks you through how to estimate fixed and variable cost components from regression output. You'll learn how to interpret the y-intercept as fixed cost, read the slope coefficient as variable cost per unit, and correctly distinguish the correlation coefficient (R) from the coefficient of determination (R-squared) — a distinction exam candidates frequently miss. Ideal for college accounting students and CPA, CMA, and EA candidates studying cost accounting and managerial accounting decision-making.
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Video Timeline & Key Concepts:
0:00 — Introduction to the regression cost-estimation MCQ
0:39 — Y-intercept as the estimate of fixed costs
0:55 — Slope coefficient as variable cost per unit of activity
1:10 — Defining the correlation coefficient (R) and relationship strength
1:38 — Coefficient of determination (R-squared) explained
2:23 — How R reflects the proximity of data points to the regression line
Frequently Asked Questions:
Q: What does the y-intercept represent in a regression cost equation?
A: The y-intercept represents the estimated fixed cost, the portion of total cost that stays constant regardless of activity level. In the cost formula y a + bx, the term a is the fixed cost component.
Q: What is the difference between the correlation coefficient (R) and R-squared?
A: The correlation coefficient (R) measures the strength and direction of the relationship between the dependent and independent variables and ranges from 0 to 1 in absolute terms. R-squared, the coefficient of determination, tells you the proportion of the variation in the dependent variable that is explained by the independent variable.
Q: What does an R value close to 1 indicate?
A: An R value near 1 indicates a strong relationship, meaning the actual data points fall very close to the regression line and the model fits the data well. As R approaches 0, the data points scatter farther from the line and the relationship weakens.
Q: How is the variable cost per unit found from regression output?
A: The variable cost per unit is the slope coefficient of the independent variable, the term b in y a + bx. It shows how much total cost increases for each additional unit of activity.
Q: Why is regression analysis preferred over the high-low method for cost estimation?
A: Regression analysis uses all of the available data points to fit the cost line, so it generally produces a more reliable estimate of fixed and variable costs. The high-low method uses only the highest and lowest activity levels, which can be distorted by outliers and ignores the information contained in the other observations.
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