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Two-factor Factorial Designs

Probability and Statistics · FE Reference Handbook section

Probability and Statistics
54 formulas
10 exam-style examples
~60 min
All Probability and Statistics lectures

Handbook notes for this section

Definitions and conditions exactly as the handbook states them.

  • For a levels of Factor A, b levels of Factor B, and n repetitions per cell:
  • Montgomery, Douglas C., and George C. Runger, Applied Statistics and Probability for Engineers, 4 ed., New York: John Wiley and Sons, 2007.
  • Source of Variation Mean Square F
  • Randomized Complete Block ANOVA Table

Core formulas for this FE topic

Definitions, applicability, units, assumptions and worked examples for each relation.

Worked exam-style examples

The four ways this section is written on the real exam — thoughts first, then equations, then substitution.

Example 1
Runs in a two-factor factorial design — solve for total experimental runs — Two-factor Factorial Designs

a concrete mix study crossing cement type with curing regime Given levels of factor A (a) = 5.0000; levels of factor B (b) = 4.0000; replicates per cell (n) = 3.0000, determine the total experimental runs (N) in runs.

Given

  • levelsoffactorA(a)=5.0000levels of factor A (a) = 5.0000
  • levelsoffactorB(b)=4.0000levels of factor B (b) = 4.0000
  • replicatespercell(n)=3.0000replicates per cell (n) = 3.0000

Find

total experimental runs (N), in runs

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except N is given, so isolate N symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for N:

    N=abnN = a b n
  3. Step 3 — List the givens: levels of factor A (a) = 5.0000, levels of factor B (b) = 4.0000, replicates per cell (n) = 3.0000.

  4. Step 4 — Substitute the given values:

    N=5.00004.00003.0000N = 5.0000 4.0000 3.0000
  5. Step 5 — Evaluate:

    N=60.0000 runsN = 60.0000\ \text{runs}
  6. Step 6 — Check: returning N = 60.0000 runs to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
N=60.0000 runsN = 60.0000\ \text{runs}

Why the other options are there

  • 120.0 — kept a factor of two that cancels in the correct rearrangement.
  • 30.0000 — dropped that same factor in the other direction.
  • 66.0000 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

Example 2
Runs in a two-factor factorial design — solve for replicates per cell — Two-factor Factorial Designs (2)

an asphalt study crossing binder grade with compaction effort Given total experimental runs (N) = 56.0000 runs; levels of factor A (a) = 5.0000; levels of factor B (b) = 2.0000, determine the replicates per cell (n).

Given

  • totalexperimentalruns(N)=56.0000runstotal experimental runs (N) = 56.0000 runs
  • levelsoffactorA(a)=5.0000levels of factor A (a) = 5.0000
  • levelsoffactorB(b)=2.0000levels of factor B (b) = 2.0000

Find

replicates per cell (n)

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except n is given, so isolate n symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for n:

    n=Nabn = \dfrac{N}{a b}
  3. Step 3 — List the givens: total experimental runs (N) = 56.0000 runs, levels of factor A (a) = 5.0000, levels of factor B (b) = 2.0000.

  4. Step 4 — Substitute the given values:

    n=56.00005.00002.0000n = \dfrac{56.0000}{5.0000 2.0000}
  5. Step 5 — Evaluate:

    n=5.6000n = 5.6000
  6. Step 6 — Check: returning n = 5.6000 to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
n=5.6000n = 5.6000

Why the other options are there

  • 11.2000 — kept a factor of two that cancels in the correct rearrangement.
  • 2.8000 — dropped that same factor in the other direction.
  • 6.1600 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

Example 3
Runs in a two-factor factorial design — solve for levels of factor B — Two-factor Factorial Designs (3)

a soil study crossing compaction energy with moisture level Given total experimental runs (N) = 140.0 runs; levels of factor A (a) = 4.0000; replicates per cell (n) = 5.0000, determine the levels of factor B (b).

Given

  • totalexperimentalruns(N)=140.0runstotal experimental runs (N) = 140.0 runs
  • levelsoffactorA(a)=4.0000levels of factor A (a) = 4.0000
  • replicatespercell(n)=5.0000replicates per cell (n) = 5.0000

Find

levels of factor B (b)

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except b is given, so isolate b symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for b:

    b=Nanb = \dfrac{N}{a n}
  3. Step 3 — List the givens: total experimental runs (N) = 140.0 runs, levels of factor A (a) = 4.0000, replicates per cell (n) = 5.0000.

  4. Step 4 — Substitute the given values:

    b=140.04.00005.0000b = \dfrac{140.0}{4.0000 5.0000}
  5. Step 5 — Evaluate:

    b=7.0000b = 7.0000
  6. Step 6 — Check: returning b = 7.0000 to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
b=7.0000b = 7.0000

Why the other options are there

  • 14.0000 — kept a factor of two that cancels in the correct rearrangement.
  • 3.5000 — dropped that same factor in the other direction.
  • 7.7000 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

Example 4
Runs in a two-factor factorial design — solve for total experimental runs (case 2) — Two-factor Factorial Designs (4)

a concrete mix study crossing cement type with curing regime Given levels of factor A (a) = 5.0000; levels of factor B (b) = 4.0000; replicates per cell (n) = 2.0000, determine the total experimental runs (N) in runs.

Given

  • levelsoffactorA(a)=5.0000levels of factor A (a) = 5.0000
  • levelsoffactorB(b)=4.0000levels of factor B (b) = 4.0000
  • replicatespercell(n)=2.0000replicates per cell (n) = 2.0000

Find

total experimental runs (N), in runs

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except N is given, so isolate N symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for N:

    N=abnN = a b n
  3. Step 3 — List the givens: levels of factor A (a) = 5.0000, levels of factor B (b) = 4.0000, replicates per cell (n) = 2.0000.

  4. Step 4 — Substitute the given values:

    N=5.00004.00002.0000N = 5.0000 4.0000 2.0000
  5. Step 5 — Evaluate:

    N=40.0000 runsN = 40.0000\ \text{runs}
  6. Step 6 — Check: returning N = 40.0000 runs to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
N=40.0000 runsN = 40.0000\ \text{runs}

Why the other options are there

  • 80.0000 — kept a factor of two that cancels in the correct rearrangement.
  • 20.0000 — dropped that same factor in the other direction.
  • 44.0000 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

Example 5
Runs in a two-factor factorial design — solve for replicates per cell (case 2) — Two-factor Factorial Designs (5)

an asphalt study crossing binder grade with compaction effort Given total experimental runs (N) = 62.0000 runs; levels of factor A (a) = 4.0000; levels of factor B (b) = 2.0000, determine the replicates per cell (n).

Given

  • totalexperimentalruns(N)=62.0000runstotal experimental runs (N) = 62.0000 runs
  • levelsoffactorA(a)=4.0000levels of factor A (a) = 4.0000
  • levelsoffactorB(b)=2.0000levels of factor B (b) = 2.0000

Find

replicates per cell (n)

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except n is given, so isolate n symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for n:

    n=Nabn = \dfrac{N}{a b}
  3. Step 3 — List the givens: total experimental runs (N) = 62.0000 runs, levels of factor A (a) = 4.0000, levels of factor B (b) = 2.0000.

  4. Step 4 — Substitute the given values:

    n=62.00004.00002.0000n = \dfrac{62.0000}{4.0000 2.0000}
  5. Step 5 — Evaluate:

    n=7.7500n = 7.7500
  6. Step 6 — Check: returning n = 7.7500 to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
n=7.7500n = 7.7500

Why the other options are there

  • 15.5000 — kept a factor of two that cancels in the correct rearrangement.
  • 3.8750 — dropped that same factor in the other direction.
  • 8.5250 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

Example 6
Runs in a two-factor factorial design — solve for levels of factor B (case 2) — Two-factor Factorial Designs (6)

a soil study crossing compaction energy with moisture level Given total experimental runs (N) = 120.0 runs; levels of factor A (a) = 2.0000; replicates per cell (n) = 2.0000, determine the levels of factor B (b).

Given

  • totalexperimentalruns(N)=120.0runstotal experimental runs (N) = 120.0 runs
  • levelsoffactorA(a)=2.0000levels of factor A (a) = 2.0000
  • replicatespercell(n)=2.0000replicates per cell (n) = 2.0000

Find

levels of factor B (b)

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except b is given, so isolate b symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for b:

    b=Nanb = \dfrac{N}{a n}
  3. Step 3 — List the givens: total experimental runs (N) = 120.0 runs, levels of factor A (a) = 2.0000, replicates per cell (n) = 2.0000.

  4. Step 4 — Substitute the given values:

    b=120.02.00002.0000b = \dfrac{120.0}{2.0000 2.0000}
  5. Step 5 — Evaluate:

    b=30.0000b = 30.0000
  6. Step 6 — Check: returning b = 30.0000 to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
b=30.0000b = 30.0000

Why the other options are there

  • 60.0000 — kept a factor of two that cancels in the correct rearrangement.
  • 15.0000 — dropped that same factor in the other direction.
  • 33.0000 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

Example 7
Runs in a two-factor factorial design — solve for total experimental runs (case 3) — Two-factor Factorial Designs (7)

a concrete mix study crossing cement type with curing regime Given levels of factor A (a) = 3.0000; levels of factor B (b) = 4.0000; replicates per cell (n) = 4.0000, determine the total experimental runs (N) in runs.

Given

  • levelsoffactorA(a)=3.0000levels of factor A (a) = 3.0000
  • levelsoffactorB(b)=4.0000levels of factor B (b) = 4.0000
  • replicatespercell(n)=4.0000replicates per cell (n) = 4.0000

Find

total experimental runs (N), in runs

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except N is given, so isolate N symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for N:

    N=abnN = a b n
  3. Step 3 — List the givens: levels of factor A (a) = 3.0000, levels of factor B (b) = 4.0000, replicates per cell (n) = 4.0000.

  4. Step 4 — Substitute the given values:

    N=3.00004.00004.0000N = 3.0000 4.0000 4.0000
  5. Step 5 — Evaluate:

    N=48.0000 runsN = 48.0000\ \text{runs}
  6. Step 6 — Check: returning N = 48.0000 runs to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
N=48.0000 runsN = 48.0000\ \text{runs}

Why the other options are there

  • 96.0000 — kept a factor of two that cancels in the correct rearrangement.
  • 24.0000 — dropped that same factor in the other direction.
  • 52.8000 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

Example 8
Runs in a two-factor factorial design — solve for replicates per cell (case 3) — Two-factor Factorial Designs (8)

an asphalt study crossing binder grade with compaction effort Given total experimental runs (N) = 178.0 runs; levels of factor A (a) = 3.0000; levels of factor B (b) = 3.0000, determine the replicates per cell (n).

Given

  • totalexperimentalruns(N)=178.0runstotal experimental runs (N) = 178.0 runs
  • levelsoffactorA(a)=3.0000levels of factor A (a) = 3.0000
  • levelsoffactorB(b)=3.0000levels of factor B (b) = 3.0000

Find

replicates per cell (n)

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except n is given, so isolate n symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for n:

    n=Nabn = \dfrac{N}{a b}
  3. Step 3 — List the givens: total experimental runs (N) = 178.0 runs, levels of factor A (a) = 3.0000, levels of factor B (b) = 3.0000.

  4. Step 4 — Substitute the given values:

    n=178.03.00003.0000n = \dfrac{178.0}{3.0000 3.0000}
  5. Step 5 — Evaluate:

    n=19.7778n = 19.7778
  6. Step 6 — Check: returning n = 19.7778 to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
n=19.7778n = 19.7778

Why the other options are there

  • 39.5556 — kept a factor of two that cancels in the correct rearrangement.
  • 9.8889 — dropped that same factor in the other direction.
  • 21.7556 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

Example 9
Runs in a two-factor factorial design — solve for levels of factor B (case 3) — Two-factor Factorial Designs (9)

a soil study crossing compaction energy with moisture level Given total experimental runs (N) = 136.0 runs; levels of factor A (a) = 5.0000; replicates per cell (n) = 2.0000, determine the levels of factor B (b).

Given

  • totalexperimentalruns(N)=136.0runstotal experimental runs (N) = 136.0 runs
  • levelsoffactorA(a)=5.0000levels of factor A (a) = 5.0000
  • replicatespercell(n)=2.0000replicates per cell (n) = 2.0000

Find

levels of factor B (b)

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except b is given, so isolate b symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for b:

    b=Nanb = \dfrac{N}{a n}
  3. Step 3 — List the givens: total experimental runs (N) = 136.0 runs, levels of factor A (a) = 5.0000, replicates per cell (n) = 2.0000.

  4. Step 4 — Substitute the given values:

    b=136.05.00002.0000b = \dfrac{136.0}{5.0000 2.0000}
  5. Step 5 — Evaluate:

    b=13.6000b = 13.6000
  6. Step 6 — Check: returning b = 13.6000 to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
b=13.6000b = 13.6000

Why the other options are there

  • 27.2000 — kept a factor of two that cancels in the correct rearrangement.
  • 6.8000 — dropped that same factor in the other direction.
  • 14.9600 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

Example 10
Runs in a two-factor factorial design — solve for total experimental runs (case 4) — Two-factor Factorial Designs (10)

a concrete mix study crossing cement type with curing regime Given levels of factor A (a) = 4.0000; levels of factor B (b) = 5.0000; replicates per cell (n) = 5.0000, determine the total experimental runs (N) in runs.

Given

  • levelsoffactorA(a)=4.0000levels of factor A (a) = 4.0000
  • levelsoffactorB(b)=5.0000levels of factor B (b) = 5.0000
  • replicatespercell(n)=5.0000replicates per cell (n) = 5.0000

Find

total experimental runs (N), in runs

Start with the thinking

  • The governing relation printed in this handbook section is Runs in a two-factor factorial design.
  • Everything except N is given, so isolate N symbolically first — never rearrange after the numbers are in.
  • Tabulate each given with its unit and confirm the units are consistent with the relation before substituting.
  • A two-factor factorial design tests every level combination of two factors with n replicates per cell.

Step-by-step solution

  1. Step 1 — State the governing relation:

    N=abnN = a b n
  2. Step 2 — Rearrange symbolically for N:

    N=abnN = a b n
  3. Step 3 — List the givens: levels of factor A (a) = 4.0000, levels of factor B (b) = 5.0000, replicates per cell (n) = 5.0000.

  4. Step 4 — Substitute the given values:

    N=4.00005.00005.0000N = 4.0000 5.0000 5.0000
  5. Step 5 — Evaluate:

    N=100.0 runsN = 100.0\ \text{runs}
  6. Step 6 — Check: returning N = 100.0 runs to

    N=abnN = a b n

    reproduces the given quantities, and both sides carry the same units.

Answer:
N=100.0 runsN = 100.0\ \text{runs}

Why the other options are there

  • 200.0 — kept a factor of two that cancels in the correct rearrangement.
  • 50.0000 — dropped that same factor in the other direction.
  • 110.0 — rounded an intermediate value before the final step.

Reference: FE Handbook — Two-factor Factorial Designs

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