Managerial Accounting - Module 2 (Ch. 18) Sec. 2:

Introduction

• Presenter: Larry Walther
• Topic: Cost Behavior
• Previous Module: Definitions of fixed cost and variable cost

Mixed Costs

• Definition: Costs that are neither strictly fixed nor strictly variable.
• Example: Butler's Car Wash
  • Water supply contract: $1,000 flat fee + $3 per 1,000 gallons used
  • Costs plotted in a spreadsheet:
    • Column A: Gallons used
    • Column B: Variable cost
    • Column C: Fixed cost
    • Total cost: Accumulation of Columns B and C
• Graph: Shows total water cost starting at $1,000 (fixed cost) and increasing linearly with variable cost.

Analyzing Mixed Costs

• Challenge: Costs not clearly fixed or variable.
• High-Low Method: Separates total cost into fixed and variable components
  • Steps:
    1. Identify highest and lowest levels of activity and their costs
    2. Calculate difference in cost and volume
    3. Determine variable cost per unit (change in cost/change in volume)
    4. Remaining amount is fixed cost
• Example:
  • Usage: 850,000 gallons (high) and 340,000 gallons (low)
  • Costs: $3,550 (high) and $2,020 (low)
  • Variable cost per unit: $3
  • Fixed cost: $1,000
• Limitations: Can be imprecise if outliers exist

Least Squares Method

• Definition: Statistically valid method based on regression analysis

  • Formula: y = a + bX
    • a: Intercept (fixed cost)
    • b: Slope (variable cost)
    • X: Volume level

• Process:

  • Data set: Monthly data on units and total costs
  • Compute regression analysis using spreadsheet software
  • Example:
    • Intercept: $138,533
    • Slope: $10.34
    • Fixed cost: $138,000
    • Variable cost: $10 per unit

• R-Squared Value: Indicates fit of the regression line

  • Example: R^2 = 0.798
  • Interpretation: 80% of variation explained by volume fluctuations
  • Higher R^2 values indicate a better fit

Scatter Graph Method

• Definition: Alternative method
• Process: Plot points on graph and draw line to approximate values

Conclusion

• High-Low Method: Simple but may be inaccurate with outliers
• Least Squares Method: More accurate, minimizes distance between data points and line
• R-Squared Value: Key indicator of goodness of fit

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End of Chapter 18 Notes.