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Session 3 of 8
Sampling
Strategies
How do you learn about a million people without asking every single one? You take a smart sample.
🔍 Data Science for Young Minds · Grade 5 — Data Detective
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Today's Plan
What We're Doing Today
- 🎯 Hook — the mystery bead jar
- 👥 Population vs. sample
- 🎲 Three sampling strategies: random, convenience, stratified
- 🫙 Bead Jar Simulation — does sample size matter?
- 📊 Calculating percentages from samples
- ✍️ Analysis: which sample was more accurate — and why?
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Opening Hook
The Mystery Jar
Your teacher is holding a jar with 100 beads — four different colors mixed together.
Without counting every single bead — how could you figure out approximately how many of each color there are?
Think about it. Then we'll test your idea.
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Lesson 1
Population vs. Sample
👥 Population
- The ENTIRE group you want to study
- All students in your school
- All 100 beads in the jar
- Every voter in a country
- Often too large to study completely
🔬 Sample
- A smaller group selected to represent the population
- 30 students from your school
- 10 beads drawn from the jar
- 1,000 randomly selected voters
- Must be chosen carefully to be useful
The key question isn't just "how big is the sample" — it's "how was the sample chosen?"
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Lesson 2
Three Sampling Strategies
🎲 Random Sample
Every member of the population has an equal chance of being selected. Most fair and least biased. Drawing names from a hat.
⚠️ Convenience Sample
You pick whoever is easiest to reach. Fast but often biased. Asking only your friends what music everyone likes.
📊 Stratified Sample
Divide the population into groups, then sample from each group proportionally. More complex but very representative.
A convenience sample can give you completely wrong results — even if you sample a lot of people. Who you ask matters as much as how many you ask.
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Lesson 2
Convenience Sampling — A Famous Failure
In 1936, a magazine called Literary Digest surveyed 2.4 million people about the upcoming US election. They predicted the wrong winner — badly.
What went wrong?
- They sent surveys to phone book owners and car owners
- In 1936, mainly wealthy people had phones and cars
- Their sample was huge — but biased toward one group
- Size didn't fix the bias
The lesson
- 2.4 million people surveyed = wrong answer
- A random sample of 50,000 = correct prediction
- HOW you sample matters more than HOW MANY
- Bias in sampling = bias in conclusions
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Lesson 3
Why Sample Size Matters Too
Once you have a random sampling method, bigger samples give more reliable results.
- 🫙 Draw 5 beads from a jar of 100: high chance of getting an unusual result
- 🫙 Draw 30 beads: much more likely to reflect true proportions
- 🫙 Draw 90 beads: very close to the truth — but a lot of work!
In real research, scientists calculate the minimum sample size needed to be confident in their results. More data = more certainty, but there's a point of diminishing returns.
Quick math: if you drew 30 beads and found 12 red, what % is that? → 12 ÷ 30 × 100 = 40%
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Activity Time!
Bead Jar Simulation
Your jar contains 100 beads of 4 colors. You don't know the true distribution — yet.
- 🫙 Round 1: Without looking, draw 10 beads. Count each color. Record on worksheet. Put them back and shake.
- 📊 Calculate: Convert each count to a percentage (count ÷ 10 × 100).
- 🫙 Round 2: Without looking, draw 30 beads. Count each color. Record. Put back and shake.
- 📊 Calculate: Convert to percentages (count ÷ 30 × 100).
- 🔍 Reveal: Your teacher will reveal the true distribution. Compare!
⏱ You have 20 minutes. Work carefully — your data is real evidence!
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🧠
Brain Break — Sample or Population?
Stand for SAMPLE, sit for POPULATION.
"All the fish in the ocean" · "50 fish caught for a study" · "Every student at your school" · "The 30 students in this class" · "Every bead in the jar" · "10 beads you just drew"
A sample is always a subset of the population it represents!
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Reveal!
The True Distribution
Here is what was actually in your jar:
Compare to YOUR results. Which of your samples was closer — 10 beads or 30 beads?
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Debrief
What Did Your Data Show?
"Which sample size was closer to the true distribution? Why do you think that happened? Did anyone get a surprising result with 10 beads?"
- How far off was your 10-bead sample for each color?
- How far off was your 30-bead sample?
- If you had drawn 5 beads, what might have happened?
- Could a 10-bead sample ever be exactly right? Is that luck or skill?
This is why scientists don't trust tiny samples — even when the results look perfect.
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Lesson 4
What Makes a Sample Representative?
- 🎲 It must be selected randomly — not by who's convenient or who volunteers
- 📏 It must be large enough to capture the variation in the population
- 🔁 It must reflect the proportions of different groups in the population
- 🚫 Avoid self-selection bias — when only certain people choose to respond
Real-world example: A poll of 10,000 people who all watch the same TV show is less representative than a random poll of 500 people from the general population.
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Analysis Time
Your Written Analysis
"Which sample size gave you a more accurate picture — 10 beads or 30? Use your actual data to explain. What would happen with 50 beads? 90?"
✍️ 5 minutes. Use your worksheet — Part 4. Cite your actual percentages. Don't just say "30 was better" — show it with numbers.
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Vocabulary Check
Session 3 Key Terms
Population
The entire group you want to study or learn about
Sample
A smaller group selected to represent the population
Random Sample
Every member has an equal chance of being selected
Convenience Sample
Whoever is easiest to reach — often biased
Representative
Reflects the true proportions of the population
Sample Size
The number of individuals in the sample
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Session Close
The Sampling Detective Rule
"Ask not just how many — ask how they were chosen."
- ✅ You can explain population vs. sample
- ✅ You can compare random, convenience, and stratified sampling
- ✅ You've seen firsthand why sample size matters
- ✅ You can convert sample counts to percentages
Next session: Even a perfectly collected sample can be used to mislead. We become Data Detectives and catch the tricks.