Understanding Tests of Proportions :Designing, Running, and Analyzing Experiments(Interaction Design Specialization) Answers 2026

Question 1

Why recode Subject column using factor()?

❌ Nominal, not numeric
❌ Categorical, not numeric
❌ Nominal, not scalar
❌ Categorical, not scalar
✅ All of the above

Explanation:
Subject IDs are categorical identifiers, not quantities, even if encoded as numbers.

Question 2

Variable type names that are synonyms (Select all that apply)

✅ Categorical, nominal, factor
✅ Ordinal, ordered
✅ Numeric, continuous, scalar
❌ Numeric, ordinal, factor
❌ Categorical, binomial, scalar

Question 3

Correct R command for viewing preference proportions:

❌ plot(data$Pref)
❌ boxplot(data$Pref)
❌ plot(data$Subject)
❌ boxplot(data$Subject)
✅ None of the above

(Typically you’d use prop.table(table(data$Pref)))

Question 4

Most precise description of a one-sample test of proportions:

❌ Proportions are different
❌ Proportions differ from each other
✅ Whether any proportions differ significantly from chance
❌ Proportions differ from each other
❌ None

Question 5

Most proper way to report Chi-Square result:

❌ χ²(1,20) = 4.12, p<.05
❌ χ²(1,20) = 4.12, p=.04257
❌ χ²(1,N=20) = 4.12, p<.05
✅ χ²(1,N=20) = 4.12, p=.04257
❌ None

Question 6

What does “n.s.” mean?

✅ Non-significant
❌ Not statistical
❌ Insignificant
❌ Nae significaté
❌ Not shown

Question 7

Main purpose of inferential statistical tests:

❌ Prove two things are different
❌ Prove two things are equal
✅ Provide evidence that two things are different
❌ Provide evidence they’re not detectably different
❌ Prove they’re not detectably different

Question 8

Exact tests compute:

✅ An exact p-value
❌ Exact Chi value
❌ Exact degrees of freedom
❌ Exact binomial value
❌ None

Question 9

Binomial test is used for two response categories:

✅ True
❌ False

Question 10

Multinomial test generalizes binomial test:

✅ True
❌ False

Question 11

No-preference probabilities for 4 categories:

❌ c(1/4,1/4,1/4)
❌ c(1/3,1/3,1/3)
❌ c(1/2,1/4,1/4)
❌ c(1/2,1/2)
✅ c(1/4,1/4,1/4,1/4)

Question 12

Omnibus test compares two levels of a three-level factor:

❌ True
✅ False

Question 13

True statements about post hoc tests (Select all that apply)

✅ Justified after a significant overall test
✅ Justified after a significant omnibus test
✅ Compare specific levels of a factor
✅ Often pairwise comparisons
✅ May use a different test than the omnibus test

Question 14

Best explanation of post hoc adjustments:

❌ Make p-values bigger
❌ Improve chances of finding significance
✅ Reduce Type I error from multiple comparisons
❌ Reduce Type II error
❌ Make p-values smaller

Question 15

“holm” adjustment stands for:

❌ Bonferroni correction
❌ Holm-Bonferroni school
❌ Holm’s statistical test
✅ Holm’s sequential Bonferroni procedure
❌ None

Question 16

Which indicate two-sample proportions (Select all that apply)

❌ Choices among three options by degree
❌ Choices among two options
❌ Reduce to two options then choose
❌ Choices among three options by citizenship
✅ Choices among two options by degree AND citizenship

Question 17

Tests of proportions reviewed (Select all that apply)

✅ Chi-Square test
❌ A/B test
✅ Binomial test
✅ G-test
❌ Friedman test

Question 18

The G-test is essentially a newer version of:

✅ Chi-Square test
❌ A/B test
❌ Binomial test
❌ t-test
❌ Turing test

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