DSC1520 - Quantitative Modelling I (LJU4801)
Exam Prep 2025–2026 | Verified Application
Questions with Correct Answers & Detailed
Rationales | Comprehensive UNISA Study Guide for
Quantitative Techniques and Decision Analysis
Question 1:
What is the primary purpose of quantitative modeling?
A) To create visual representations
B) To analyze data and make predictions using mathematical techniques
C) To simplify complex problems
D) To enhance communication
Rationale: Quantitative modeling helps in decision-making by analyzing numerical data
and predicting future outcomes.
Question 2:
What is a "linear model"?
A) A model with exponential relationships
B) A model that describes a relationship using a linear equation
C) A non-linear model
D) A model focused on qualitative data
Rationale: Linear models represent relationships in a straight-line format, aiding in
understanding direct proportionality.
Question 3:
What does "sensitivity analysis" assess?
A) The accuracy of predictions
B) How changes in input variables affect outputs in a model
C) The validity of data sources
D) The complexity of a model
Rationale: Sensitivity analysis helps identify which variables have the most impact on
outcomes.
Question 4:
What is a "decision variable"?
A) A fixed parameter in a model
B) A variable that a decision-maker can control or manipulate
,C) An irrelevant factor
D) A constant value
Rationale: Decision variables are critical in optimization problems as they determine
the outcome of the model.
Question 5:
What is meant by "objective function" in optimization?
A) A statement of constraints
B) The function that needs to be maximized or minimized
C) A fixed parameter
D) An unrelated variable
Rationale: The objective function represents the goal of the optimization process,
guiding decision-making.
Question 6:
What does "constraint" refer to in a linear programming problem?
A) An irrelevant factor
B) Restrictions or limitations placed on decision variables
C) The objective function
D) A fixed parameter
Rationale: Constraints define the boundaries within which a solution must be found in
optimization problems.
Question 7:
What is a "feasible solution"?
A) A suboptimal solution
B) A solution that satisfies all constraints in a model
C) An irrelevant variable
D) A solution that ignores constraints
Rationale: A feasible solution meets all the requirements set by the constraints of the
model.
Question 8:
What is "integer programming"?
A) A type of linear programming where some or all decision variables must take on
integer values
,B) A non-linear approach
C) A method for qualitative data
D) A fixed variable model
Rationale: Integer programming is used in scenarios where solutions must be whole
numbers, such as scheduling or resource allocation.
Question 9:
What does "objective function sensitivity" analyze?
A) The stability of constraints
B) How changes in the coefficients of the objective function affect the solution
C) The accuracy of data
D) The complexity of the model
Rationale: Understanding objective function sensitivity is crucial for determining how
robust the optimal solution is to changes.
Question 10:
What is "multi-objective optimization"?
A) Optimization involving multiple conflicting objectives
B) A single goal optimization
C) A fixed parameter model
D) A non-linear approach
Rationale: Multi-objective optimization seeks to find solutions that balance trade-offs
between different objectives.
Question 11:
What is the purpose of a "constraint matrix"?
A) To list all decision variables
B) To represent the coefficients of decision variables in constraints
C) To outline the objective function
D) To summarize results
Rationale: The constraint matrix is essential for formulating linear programming
problems in matrix form.
Question 12:
What does "linear programming" help optimize?
, A) Only qualitative outcomes
B) Resources, costs, or profits in a linear relationship
C) Non-linear relationships
D) Fixed values
Rationale: Linear programming is a mathematical method used to determine the best
outcome in a given situation with linear constraints.
Question 13:
What is a "slack variable"?
A) A decision variable
B) A variable added to a constraint to convert it into an equality
C) An irrelevant factor
D) A fixed parameter
Rationale: Slack variables represent unused resources in resource allocation
problems.
Question 14:
What does "dual problem" refer to in linear programming?
A) A non-linear approach
B) A problem derived from the original (primal) linear programming problem
C) A fixed variable model
D) An irrelevant factor
Rationale: The dual problem provides insights into the original problem's constraints
and objective function.
Question 15:
What is "goal programming"?
A) A single-objective optimization method
B) A multi-objective optimization technique that prioritizes goals
C) A method for qualitative data
D) A fixed variable model
Rationale: Goal programming helps find solutions that meet multiple goals while
considering their importance.
Question 16:
What is a "simulation model"?
Exam Prep 2025–2026 | Verified Application
Questions with Correct Answers & Detailed
Rationales | Comprehensive UNISA Study Guide for
Quantitative Techniques and Decision Analysis
Question 1:
What is the primary purpose of quantitative modeling?
A) To create visual representations
B) To analyze data and make predictions using mathematical techniques
C) To simplify complex problems
D) To enhance communication
Rationale: Quantitative modeling helps in decision-making by analyzing numerical data
and predicting future outcomes.
Question 2:
What is a "linear model"?
A) A model with exponential relationships
B) A model that describes a relationship using a linear equation
C) A non-linear model
D) A model focused on qualitative data
Rationale: Linear models represent relationships in a straight-line format, aiding in
understanding direct proportionality.
Question 3:
What does "sensitivity analysis" assess?
A) The accuracy of predictions
B) How changes in input variables affect outputs in a model
C) The validity of data sources
D) The complexity of a model
Rationale: Sensitivity analysis helps identify which variables have the most impact on
outcomes.
Question 4:
What is a "decision variable"?
A) A fixed parameter in a model
B) A variable that a decision-maker can control or manipulate
,C) An irrelevant factor
D) A constant value
Rationale: Decision variables are critical in optimization problems as they determine
the outcome of the model.
Question 5:
What is meant by "objective function" in optimization?
A) A statement of constraints
B) The function that needs to be maximized or minimized
C) A fixed parameter
D) An unrelated variable
Rationale: The objective function represents the goal of the optimization process,
guiding decision-making.
Question 6:
What does "constraint" refer to in a linear programming problem?
A) An irrelevant factor
B) Restrictions or limitations placed on decision variables
C) The objective function
D) A fixed parameter
Rationale: Constraints define the boundaries within which a solution must be found in
optimization problems.
Question 7:
What is a "feasible solution"?
A) A suboptimal solution
B) A solution that satisfies all constraints in a model
C) An irrelevant variable
D) A solution that ignores constraints
Rationale: A feasible solution meets all the requirements set by the constraints of the
model.
Question 8:
What is "integer programming"?
A) A type of linear programming where some or all decision variables must take on
integer values
,B) A non-linear approach
C) A method for qualitative data
D) A fixed variable model
Rationale: Integer programming is used in scenarios where solutions must be whole
numbers, such as scheduling or resource allocation.
Question 9:
What does "objective function sensitivity" analyze?
A) The stability of constraints
B) How changes in the coefficients of the objective function affect the solution
C) The accuracy of data
D) The complexity of the model
Rationale: Understanding objective function sensitivity is crucial for determining how
robust the optimal solution is to changes.
Question 10:
What is "multi-objective optimization"?
A) Optimization involving multiple conflicting objectives
B) A single goal optimization
C) A fixed parameter model
D) A non-linear approach
Rationale: Multi-objective optimization seeks to find solutions that balance trade-offs
between different objectives.
Question 11:
What is the purpose of a "constraint matrix"?
A) To list all decision variables
B) To represent the coefficients of decision variables in constraints
C) To outline the objective function
D) To summarize results
Rationale: The constraint matrix is essential for formulating linear programming
problems in matrix form.
Question 12:
What does "linear programming" help optimize?
, A) Only qualitative outcomes
B) Resources, costs, or profits in a linear relationship
C) Non-linear relationships
D) Fixed values
Rationale: Linear programming is a mathematical method used to determine the best
outcome in a given situation with linear constraints.
Question 13:
What is a "slack variable"?
A) A decision variable
B) A variable added to a constraint to convert it into an equality
C) An irrelevant factor
D) A fixed parameter
Rationale: Slack variables represent unused resources in resource allocation
problems.
Question 14:
What does "dual problem" refer to in linear programming?
A) A non-linear approach
B) A problem derived from the original (primal) linear programming problem
C) A fixed variable model
D) An irrelevant factor
Rationale: The dual problem provides insights into the original problem's constraints
and objective function.
Question 15:
What is "goal programming"?
A) A single-objective optimization method
B) A multi-objective optimization technique that prioritizes goals
C) A method for qualitative data
D) A fixed variable model
Rationale: Goal programming helps find solutions that meet multiple goals while
considering their importance.
Question 16:
What is a "simulation model"?
