Introduction: Why Sampling Matters in AP Statistics
Sampling is one of the first topics in AP Statistics and sets the foundation for everything else — probability, inference, surveys, and experiments. Many FRQs and MCQs test your ability to:
- Identify different sampling methods.
- Recognize bias in poorly designed samples.
- Apply sampling strategies to real-world problems.
This guide explains all the major AP Statistics sampling methods, gives examples, and shows you how to write about them effectively on the AP exam.
Step 1: Why Do We Sample?
- Populations are often too large to measure entirely.
- Sampling saves time, money, and effort.
- Good sampling = accurate, unbiased estimates.
- Bad sampling = bias, incorrect conclusions.
👉 On the AP exam, questions often ask you to identify bias or describe how to take a sample properly.
Step 2: Types of Sampling Methods
1. Simple Random Sample (SRS)
- Definition: Every individual has an equal chance of selection.
- Example: Drawing names from a hat of all students in a school.
- Advantage: Minimizes bias.
- Disadvantage: Hard to implement with large populations.
👉 On FRQs: Explain how to randomize (random number generator, random digit table).
2. Stratified Random Sample
- Definition: Population divided into strata (groups), then SRS taken from each.
- Example: Splitting students by grade, then randomly selecting from each grade.
- Advantage: Ensures representation of all subgroups.
- Disadvantage: Requires knowing population structure.
👉 Common FRQ: “Describe how you would take a stratified random sample of 100 households in a city.”
3. Cluster Sample
- Definition: Population divided into clusters, then entire clusters randomly selected.
- Example: Randomly selecting 5 classrooms and surveying every student in them.
- Advantage: Efficient for large populations.
- Disadvantage: May not represent whole population well if clusters are similar internally.
4. Systematic Sample
- Definition: Select every k-th member after a random start.
- Example: At a concert, survey every 10th person entering.
- Advantage: Easy to implement.
- Disadvantage: Can be biased if there’s a pattern in the population.
5. Convenience Sample (Bad)
- Definition: Choosing individuals easiest to reach.
- Example: Asking only friends about school lunch.
- Bias: Overrepresents certain groups.
6. Voluntary Response Sample (Bad)
- Definition: People choose to participate.
- Example: Online survey open to anyone.
- Bias: Overrepresents those with strong opinions.
Step 3: Identifying Bias
On the exam, you’ll need to explain why a sample is biased.
Example: “A newspaper posts an online poll asking if readers support a new law.”
- Biased because voluntary response → overrepresents strong opinions.
👉 RevisionDojo’s Bias Spotting Drills give you practice identifying flawed samples.
Step 4: Writing About Sampling on FRQs
The College Board wants complete sentences with context.
Weak: “Use stratified sampling.”
Strong: “Divide the students into four strata by grade level, then randomly select 25 students from each grade using a random number generator.”
👉 RevisionDojo’s FRQ Writing Hub has model sample descriptions.
Step 5: Practice Questions
Question 1
A school wants to survey students about cafeteria food. Which method ensures representation from every grade?
- A) SRS
- B) Stratified
- C) Cluster
- D) Convenience
Answer: B (Stratified).
Question 2
A researcher surveys every 20th shopper entering a store. Which method?
- A) Cluster
- B) Systematic
- C) SRS
- D) Voluntary Response
Answer: B (Systematic).
Question 3
A company randomly selects 10 offices out of 200 and surveys all workers in them. Which method?
- A) Stratified
- B) Cluster
- C) SRS
- D) Convenience
Answer: B (Cluster).
Question 4
Which method is most prone to bias?
- A) SRS
- B) Stratified
- C) Voluntary Response
- D) Cluster
Answer: C (Voluntary Response).
Step 6: Common Mistakes to Avoid
- Confusing stratified vs cluster.
- Stratified = sample some from all groups.
- Cluster = sample all from some groups.
- Forgetting to mention randomization.
- Using convenience/voluntary response as if valid.
Step 7: How Sampling Connects to the Exam
- MCQs: Identify sampling methods, find bias.
- FRQs: Design and describe sampling process in context.
- Investigative Task: May require comparing two sampling methods.
👉 RevisionDojo provides past FRQs with sample responses.
Step 8: Study Plan for Sampling Mastery
- Memorize definitions + one example each.
- Practice writing FRQ-style sampling designs.
- Drill identifying bias in flawed surveys.
- Use RevisionDojo’s sampling flashcards.
RevisionDojo Resources
- Sampling Flashcards: Definitions + examples.
- FRQ Bank: Sampling design problems.
- Bias Drills: Spot flawed survey setups.
- Practice Quizzes: Stratified vs cluster recognition.
👉 Check out RevisionDojo’s Sampling Methods Hub here.
Frequently Asked Questions (FAQs)
Q: What’s the difference between stratified and cluster sampling?
A: Stratified = sample some from all groups. Cluster = sample all from some groups.
Q: Is systematic sampling valid for AP Stats?
A: Yes, if random start is used and no pattern exists in population.
Q: Why is voluntary response bad?
A: Overrepresents strong opinions — not representative.
Q: Do I always need to randomize?
A: Yes, randomization ensures unbiased selection.
Q: Will there always be a sampling question on the AP exam?
A: Almost always — at least in MCQs, sometimes FRQs.
Final Thoughts
Sampling methods are fundamental to AP Statistics and appear frequently on both multiple choice and FRQs.
Remember:
- SRS, stratified, cluster, systematic = good.
- Convenience, voluntary response = biased.
- Always explain randomization and context.
With RevisionDojo’s flashcards, FRQ practice, and bias drills, you’ll turn sampling questions into guaranteed points.
