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ASRB Agricultural Research Service Response Surface, Mixture & Optimal Designs: practice questions

ASRB Agricultural Research Service (ARS) - Agricultural Statistics scientist · India · Agricultural Scientists Recruitment Board (ICAR)

Original practice questions written to the published syllabus · not past papers
10worked here, free
79written to this exam in this subject
9syllabus units

What this subject covers

Finding the best dose or combination: first- and second-order response surfaces, central composite and Box-Behnken designs, rotatability, fertiliser response optimisation, mixture designs for blends and feed formulations, and the alphabetic optimality criteria.

In the exams: Not an explicit unit in AICE-JRF Ag Stat; standard MSc/PhD course in agricultural statistics programmes; ASRB NET Ag Stat (reported)

Where the 79 questions fall

How our questions for ASRB Agricultural Research Service spread across the units of Response Surface, Mixture & Optimal Designs. Difficulty: 15 easy, 45 medium, 19 hard.

Central composite and Box-Behnken designs11
Canonical analysis and the method of steepest ascent11
Mixture experiments: simplex lattice and simplex centroid designs11
First-order and second-order response surface models10
Rotatability and orthogonal blocking10
Optimality criteria: A-, D-, E- and G-optimality9
Taguchi and robust parameter designs (introduction)9
Computer-generated optimal designs7
Fertiliser response functions and economic optimum dose1

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 · First-order and second-order response surface models · hard

A 2^2 factorial has mean 40.0 at its four corners; 5 centre points have mean 44.0 and SD 1.5. What is the t statistic for curvature?

  1. 3.77
  2. 3.98
  3. 5.96
  4. 2.67
Answer and working

B. 3.98

SE = s sqrt(1/4 + 1/5) = 1.006; t = 4.0/1.006 = 3.98 on 4 df.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

2 · Rotatability and orthogonal blocking · medium

What does rotatability mean?

  1. The design can be rotated by 90 degrees only
  2. Blocks are orthogonal to the model terms
  3. Every factor has the same number of levels in the whole design
  4. Prediction variance depends only on distance from the centre
Answer and working

D. Prediction variance depends only on distance from the centre

Equal prediction precision in all directions at the same distance is rotatability.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

3 · Canonical analysis and the method of steepest ascent · medium

The eigenvalues of B are -3.0 and +1.2. What does this indicate?

  1. A minimum
  2. A rising ridge
  3. A saddle point
  4. A maximum
Answer and working

C. A saddle point

Mixed signs mean the response rises in one direction and falls in another.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

4 · Fertiliser response functions and economic optimum dose · medium

Why is a rounded fertiliser recommendation near the economic optimum usually acceptable?

  1. Fertiliser prices never change from year to year
  2. Yield response is always linear near the optimum
  3. Statistical estimates of the optimum are exact
  4. The profit curve is flat near its maximum
Answer and working

D. The profit curve is flat near its maximum

Small departures from the optimum cost little profit, and the estimate is uncertain anyway.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

5 · Optimality criteria: A-, D-, E- and G-optimality · medium

What does E-optimality maximise?

  1. The number of design points
  2. The smallest eigenvalue of X'X
  3. The average prediction variance
  4. The determinant of X'X
Answer and working

B. The smallest eigenvalue of X'X

It minimises the variance of the worst-estimated linear combination of parameters.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

6 · Optimality criteria: A-, D-, E- and G-optimality · medium

Which criterion suits an experiment whose purpose is prediction over the whole region?

  1. E-optimality
  2. Rotatability only
  3. Resolution III
  4. I-optimality
Answer and working

D. I-optimality

I-optimality minimises average prediction variance over the region.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

7 · Computer-generated optimal designs · medium

What should be checked before running a computer-generated design?

  1. Only the D-efficiency value printed by the design software
  2. Prediction variance, term correlations and lack-of-fit df
  3. Only the number of centre points in the design
  4. Only that every run uses extreme factor levels
Answer and working

B. Prediction variance, term correlations and lack-of-fit df

Optimality on one criterion does not guarantee good practical properties.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

8 · Computer-generated optimal designs · hard

A potting medium has soil at least 30%, compost 10-50% and sand at most 40%. What kind of region results?

  1. A single point
  2. An irregular polygon inside the simplex
  3. A full equilateral triangle
  4. A cube in proportion space
Answer and working

B. An irregular polygon inside the simplex

Bounds cut the simplex into a polytope, calling for vertex-based or optimal designs.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

9 · Taguchi and robust parameter designs (introduction) · medium

Which agricultural problem reflects robust-design thinking?

  1. Removing all replicates from a trial
  2. Testing a single variety at one site
  3. Practices whose yield varies little with weather
  4. Choosing the plot with the highest yield last year
Answer and working

C. Practices whose yield varies little with weather

Weather is a noise factor; practices insensitive to it are robust.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

10 · Mixture experiments: simplex lattice and simplex centroid designs · easy

What shape is the experimental region for three mixture components?

  1. A circle
  2. A cube
  3. A triangle
  4. A square
Answer and working

C. A triangle

Proportions summing to one form a two-dimensional simplex, which is a triangle.

Further reading: Myers, Montgomery and Anderson-Cook, Response Surface Methodology; Cornell, Experiments with Mixtures

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Read the subject

Response Surface, Mixture & Optimal DesignsThe full study manual, free ASRB Agricultural Research ServiceFormat, sections and how it has changed

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Response Surface, Mixture & Optimal Designs for other exams

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