Introduction: Why Misconceptions Cost Students Points
Every year, thousands of AP Statistics students lose easy points because of misconceptions — errors in logic, terminology, or interpretation. These mistakes often show up in FRQs, where graders are strict about precision.
The good news? Once you’re aware of these pitfalls, you can avoid them. This guide highlights the most common misconceptions in AP Statistics, explains why they’re wrong, and shows you how to correct them — with help from RevisionDojo’s resources.
Misconception #1: Correlation Implies Causation
- The Error: Students think if two variables are correlated, one causes the other.
- Example: Ice cream sales are correlated with drowning incidents. Does ice cream cause drowning? No — heat is a lurking variable.
- The Fix: Remember: Correlation ≠ Causation. Always consider lurking variables and context.
RevisionDojo has practice FRQs on correlation vs causation.
Misconception #2: Large Samples Guarantee No Bias
- The Error: Believing that a huge sample size eliminates bias.
- Reality: A biased method (like surveying only your friends) stays biased, no matter the size.
- The Fix: Focus on randomness, not just size. Bigger ≠ better unless the design is random.
Misconception #3: The P-Value Is the Probability That H₀ Is True
- The Error: Thinking p-value tells us the probability the null hypothesis is correct.
- Reality: The p-value measures probability of observing results as extreme as yours, assuming H₀ is true.
