Misconception Heatmap

Top 3 misconceptions per topic, shaded by % of students

0%
20%
40%
60%
70%+
TopicMisconception 1Misconception 2Misconception 3
Hypothesis Testing
Thinks p-value is probability H₀ is true
67%
Confuses α with p-value
45%
Rejects H₀ when p > α
28%
t-test vs z-test
Uses z-test when σ unknown
58%
Ignores sample size threshold
42%
Applies z-test to small samples
31%
Confidence Intervals
Thinks 95% CI means 95% chance μ is in interval
71%
Confuses CI width with confidence level
38%
Ignores sample size effect on width
25%
Type I & II Errors
Swaps Type I and Type II definitions
52%
Thinks reducing α always better
44%
Ignores power in study design
36%
Central Limit Theorem
Thinks CLT applies to any sample size
48%
Confuses σ with σ/√n
55%
Applies CLT to non-independent samples
22%
Normal Distribution
Assumes all data is normally distributed
41%
Misreads z-score direction
33%
Forgets to standardize before lookup
29%
4
days to exam

38% of students have not yet demonstrated reliable reasoning on hypothesis testing.

Top gap: interpreting p-value as P(H₀ is true), affecting 67% of the cohort

At-risk students

Taylor K.Jamie L.Avery B.Alex C.

Top Stuck Points

2-min interventions

Action items
14

Interpreting p-value as P(H₀ is true)

Quick poll: 'What does p=0.03 mean?' then show the 3 common wrong answers before the correct frequentist definition.

11

Using z-test when σ is unknown

Draw the decision tree on the board: 'Do you know σ?' → No → t-test. Takes 90 seconds.

9

Confusing CI interpretation (95% chance μ is in interval)

Simulate 20 CIs live in R/Excel. Show ~19 contain μ. 'The interval is random, not μ.'

8

Rejecting H₀ when p > α

Show an underpowered study where a real effect exists but p > α. Ask: 'Is H₀ true here?' Students see that failing to reject ≠ accepting H₀, it means insufficient evidence.

7

Swapping Type I and Type II error definitions

Use the courtroom analogy: Type I = convicting innocent (α), Type II = freeing guilty (β).

Based on 33 active students this week. Students may appear in multiple stuck points.

Students Needing Attention

12 of 47 students flagged. Click any row to see their misconceptions.

Mastered
Developing
Needs Help
StudentHypothesis Testingt-test vs z-testP-valuesConfidence IntervalsType I/II ErrorsNormal Dist.Avg
Avery Brown
35%
Taylor Kim
38%
Jamie Lee
41%
Alex Chen
45%
Morgan Davis
58%
Jordan Park
62%
Quinn Garcia
69%
Casey Williams
74%
Sam Johnson
82%
Drew Martinez
85%
Maria Santos
88%
Riley Thompson
91%

Showing 12 students flagged for attention out of 47 enrolled