In construction cost planning, probabilistic estimating incorporates uncertain inputs such as labour availability, labour productivity, and the applicable wage scale to quantify risk and expected cost—what does it typically include?

Introduction / Context:
Probabilistic estimating (also called risk-based or range estimating) recognises that construction project inputs are uncertain. Rather than a single-point number, it models a distribution of possible costs by considering variability in labour, productivity, and wage rates, along with other drivers. This question checks whether you understand the key inputs that must be treated as random variables in such an estimate.

Given Data / Assumptions:

• The project involves activities whose costs are influenced by labour hours and output rates.
• Observed variability exists in crew productivity due to learning curves, weather, congestion, and access conditions.
• Wage scale (including basic pay, allowances, and statutory burdens) can differ by trade, shift, and location.

Concept / Approach:
In probabilistic estimating, inputs are represented by probability distributions (e.g., triangular, beta-PERT, or normal). Monte Carlo simulation, or simpler range analysis, then propagates these uncertainties to the total cost. Key cost elements—crew composition (labour), their productivity (units per hour), and wage scale (₹/hour)—directly drive activity costs, so all must be included with uncertainty ranges, not as fixed values.

Step-by-Step Solution:

Verification / Alternative check:

Why Other Options Are Wrong:

Common Pitfalls:

Final Answer: