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State statistical services Optimization Techniques for Statisticians: practice questions

State statistical services: Statistical Officer / Assistant Statistical Officer (State PSCs and selection boards) · India · State Public Service Commissions and Subordinate Service Selection Boards

Original practice questions written to the published syllabus · not past papers
10worked here, free
61written to this exam in this subject
10syllabus units

What this subject covers

The optimisation theory statisticians use: linear programming with simplex and duality, transportation and assignment, integer and goal programming for farm and crop planning, non-linear optimisation with Kuhn-Tucker conditions, and the numerical optimisers inside likelihood estimation. The Agribusiness track teaches operations research for managers; this goes to the theory.

In the exams: AICE-JRF Ag Stat Unit 2 'linear programming: formulation, graphical, simplex, duality, transportation and assignment' (heavy); UPSC ISS Statistics III operations research (heavy, reported); ASRB NET Ag Stat (present)

Where the 61 questions fall

How our questions for State statistical services spread across the units of Optimization Techniques for Statisticians. Difficulty: 17 easy, 36 medium, 8 hard.

Simplex method, Big-M and two-phase methods10
Transportation and assignment problems10
Duality and sensitivity analysis9
Linear programming: formulation and graphical solution8
Integer programming: branch and bound8
Dynamic programming6
Non-linear programming: Lagrange multipliers and Kuhn-Tucker conditions4
Goal programming for multi-objective farm planning3
Quadratic programming and risk programming (MOTAD)2
Numerical optimisation: gradient, Newton and quasi-Newton methods1

10 practice questions, worked

Choose an answer, then open the working. Each explanation says why the right answer is right and why the others are not.

1 · Linear programming: formulation and graphical solution · easy

Which assumption of LP is violated when fractional animals cannot be kept?

  1. Proportionality
  2. Additivity
  3. Certainty
  4. Divisibility
Answer and working

D. Divisibility

Divisibility allows fractional activity levels; integer requirements need integer programming.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

2 · Simplex method, Big-M and two-phase methods · easy

Which variable converts a ≤ constraint into an equation in the simplex method?

  1. A dual variable
  2. A surplus variable
  3. A slack variable
  4. An artificial variable
Answer and working

C. A slack variable

Slack = unused resource, added to ≤ constraints; surplus is subtracted from ≥ constraints.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

3 · Simplex method, Big-M and two-phase methods · hard

Why do modern solvers also use interior-point methods for very large LPs?

  1. They always give integer solutions
  2. They avoid the need for constraints
  3. They give exact shadow prices without duality
  4. Polynomial worst-case complexity
Answer and working

D. Polynomial worst-case complexity

Simplex is fast in practice but has exponential worst cases; interior-point methods have polynomial complexity and suit very large sparse problems.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

4 · Transportation and assignment problems · easy

A balanced transportation problem has 3 sources and 4 destinations. How many basic (allocated) cells does a non-degenerate basic solution have?

  1. 7
  2. 6
  3. 12
  4. 4
Answer and working

B. 6

m + n − 1 = 3 + 4 − 1 = 6.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

5 · Integer programming: branch and bound · medium

A binary-variable model requires that at most 2 of 5 irrigation projects be chosen. How is this written?

  1. Σδⱼ = 2.5
  2. δ₁ + δ₂ ≤ 5
  3. δ₁δ₂ ≤ 2
  4. δ₁ + δ₂ + δ₃ + δ₄ + δ₅ ≤ 2
Answer and working

D. δ₁ + δ₂ + δ₃ + δ₄ + δ₅ ≤ 2

With δⱼ ∈ {0, 1}, the sum counts chosen projects.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

6 · Non-linear programming: Lagrange multipliers and Kuhn-Tucker conditions · medium

What does the Lagrange multiplier of a constraint measure?

  1. The number of binding constraints
  2. The constraint's marginal value
  3. The value of the objective
  4. The step size of the algorithm
Answer and working

B. The constraint's marginal value

λ = ∂f*/∂b, the shadow price of the constraint.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

7 · Dynamic programming · hard

Which methods solve a Markov decision process?

  1. Branch and bound only
  2. The simplex and MODI methods
  3. Value and policy iteration
  4. Newton-Raphson only
Answer and working

C. Value and policy iteration

Both iterate the Bellman equation for expected values.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

8 · Linear programming: formulation and graphical solution · easy

In the farm LP with 12 ha land and 16 labour-days, which constraints bind at the optimum (4, 8)?

  1. Land only
  2. Labour only
  3. Neither
  4. Both land and labour
Answer and working

D. Both land and labour

4 + 8 = 12 ha and 2 × 4 + 8 = 16 days: both resources are fully used, so both have positive shadow prices.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

9 · Duality and sensitivity analysis · easy

What is the dual of the dual of an LP?

  1. A transportation problem
  2. An integer programme
  3. The original primal
  4. The dual itself
Answer and working

C. The original primal

Duality is symmetric: dualising twice returns the primal.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

10 · Transportation and assignment problems · easy

How many possible one-to-one assignments exist for 4 tractors and 4 fields?

  1. 4
  2. 256
  3. 16
  4. 24
Answer and working

D. 24

n! = 4! = 24; 16 = 4² counts cells, not assignments.

Further reading: Taha, Operations Research: An Introduction; Hazell and Norton, Mathematical Programming for Economic Analysis in Agriculture; Nocedal and Wright, Numerical Optimization

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Optimization Techniques for StatisticiansThe full study manual, free State statistical servicesFormat, sections and how it has changed

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Optimization Techniques for Statisticians for other exams

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