Data Scout Guide Data Scout Guide
Lesson: A Fair Sample | Grade 9 Statistics
65 Minutes
Learning Objectives
• Explain why random sampling is crucial for making valid inferences.
• Identify potential sources of bias in various data collection methods.
• Distinguish between population and sample in real-world contexts.
Prep Checklist
Fair Sample Slides
Sample Swap Sort (1 set per pair)
Bias Hunter Worksheet (1 per student)
Random Check Ticket (1 per student)
Instructional Arc
1
The Pizza Dilemma (Hook) 10 Mins
Present a scenario: The school cafeteria wants to order pizza for all 2,000 students. They only have time to ask 20 people. Prompt: If they only ask the Varsity Football team, will the order reflect what the whole school wants? Why or why not?
2
Vocabulary Deep Dive 15 Mins
Use the Fair Sample Slides to define Population vs. Sample. Introduce the "Gold Standard": Simple Random Sampling . Discuss Bias as a systematic error that makes the sample not representative of the population.
3
Sample Swap Sort 15 Mins
Students work in pairs to sort scenarios into "Representative Sample" or "Biased Sample." Teacher Move: Circulate and ask, "What specific group is being excluded in this biased scenario?"
4
Bias Hunter Investigation 15 Mins
Students complete the Bias Hunter Worksheet independently. They must identify the population, sample, and explain the bias for 4 unique scenarios.
5
Synthesis & Exit 10 Mins
Quick class share-out: "What's one way to guarantee a sample is random?" (e.g., drawing names from a hat, random number generator). Distribute the Random Check Ticket .
Differentiation Strategies
Support
Provide a visual "Population vs Sample" anchor chart. Use the "Soup Taste Test" analogy: One spoonful (sample) represents the whole pot (population) only if you stir it first (randomize).
Extension
Challenge students to redesign one of the "Biased" scenarios from the worksheet to make it truly random and representative.
Fair Sample Slides Fair Sample Slides
The Art of Random Sampling
The Big Picture
Population
The entire group you want to draw conclusions about.
Example: All 2,000 students at West High.
Sample
The specific group you collect data from.
Example: 50 students chosen for a survey.
We use the Sample to make an Inference about the Population.
The Gold Standard
Simple Random Sample
A sample where every individual in the population has an equal chance of being selected.
No Favorites
No Patterns
Pure Chance
The Enemy: Bias
Bias is a systematic error that results in an unrepresentative sample.
Warning
Biased data leads to wrong conclusions. It overestimates or underestimates certain groups.
Common Bias Traps
Convenience
Choosing individuals who are easiest to reach.
Example: Surveying only your friends at lunch.
Voluntary Response
Allowing people to choose themselves.
Example: Online polls or Yelp reviews.
The Solution?
LEAVE IT TO CHANCE!
Sample Swap Sort Sample Swap Sort
Investigation Cards: Cut along the dashed lines.
Scenario A
A principal uses a computer program to randomly select 100 student ID numbers to survey about the new dress code.
Scenario B
To find out if residents want a new park, the city council surveys the first 50 people who enter the local dog park.
Scenario C
A news station asks viewers to text "YES" or "NO" to a poll about a controversial new law shown during the evening news.
Scenario D
A light bulb company tests every 500th bulb that comes off the assembly line to check for defects.
Scenario E
To see if students like the lunch options, a teacher surveys the 25 students in her AP Statistics class.
Scenario F
A researcher assigns a number to every household in a city and uses a random number generator to pick 300 of them.
Sorting Mat
Student Names: __________________________________________________ Date: ___________
Representative
Biased
Investigator Reflection
Choose one Biased scenario. Explain why it is unfair and how you would fix the sampling method to be random.
Bias Hunter Worksheet Bias Hunter
Statistical Investigation Unit
Name: __________________________
Date: __________________________
Mission: Analyze the following collection methods. Identify the target population, the actual sample used, and detect any systematic bias that prevents valid inference.
1
The Movie Buffs
"A movie theater manager wants to know the favorite genre of people in the city. He surveys every person leaving a 10:00 PM screening of a new horror movie."
Target Population:
Actual Sample:
Bias Detection & Reasoning:
2
The Commuter Pulse
"A city transportation official wants to know how people feel about public buses. They stand at a busy downtown bus stop and survey the first 100 people who get off a bus."
Target Population:
Actual Sample:
Bias Detection & Reasoning:
3
The Gym Junkies
"A fitness app company wants to know how many hours the average adult exercises per week. They send an email survey to all their active subscribers."
Target Population:
Actual Sample:
Bias Detection & Reasoning:
4
The Random Reach
"A phone company wants to know if people in a zip code prefer a new data plan. They use a computer to dial 400 randomly generated phone numbers within that zip code."
Target Population:
Actual Sample:
Bias Detection & Reasoning:
Data Scout Summary
The quality of an inference depends entirely on the quality of the sample. When bias is present, the data reflects the collection method rather than the actual population.
Challenge Mission:
Design a survey topic for your school. Describe how you would collect a Simple Random Sample of at least 50 students using a method that eliminates bias.
Random Check Ticket Exit Ticket
Random Check
Name: __________________________ Date: ________________
1. Why is a Simple Random Sample considered the "Gold Standard" in statistics?
2. Identify the bias: You want to know the school's favorite sport, so you survey only students at the basketball game.
Voluntary Response
Convenience Bias
Exit Ticket
Random Check
Name: __________________________ Date: ________________
1. Why is a Simple Random Sample considered the "Gold Standard" in statistics?
2. Identify the bias: You want to know the school's favorite sport, so you survey only students at the basketball game.
Voluntary Response
Convenience Bias
