Cost estimation is a measurement of past costs for the purpose of predicting future costs for decision-making purposes. This chapter will primarily aim at using past data to predict future costs. Various methods of cost estimation, their advantages and limitations will be discussed. The methods of cost estimation include, High Low Activity method, account analysis, engineering analysis, visual fit (scatter graph) method, simple linear regression analysis and learning curve theory.
Cost estimation may be defined as a study which attempts to predict the relationship between costs and the activity level or cost driver1 that causes those costs based on an analysis of historical costs. In other words, cost estimation occurs when an individual attempts to measure historical costs in order to predict future costs.
To achieve the measurement, it is necessary to separate cost into their fixed and variable cost elements. Semi variable costs can be separated into their fixed and variable components using scatter diagram approach, high-low method or regression analysis.
In this topic, we shall deal with linear cost relationships and equations. A linear equation is an expression of the relationship between variables, the independent and the dependent variables. The cost estimating function for linear relationships is
Y = a + bX
Analyzed as Total cost = Fixed cost + Variable cost
Y represents the dependent variable or the total cost
a represents fixed cost component of the total cost (Constant amount)
bX represents the variable costs component of the total cost
b represents the unit variable cost (this is the gradient of the equation)
x represents independent variable or the output level
This is the usual straight line equation you have been encountering in elementary mathematics.