Analyzing Samples - What’s the Most Popular Lunch?
In this engaging, data-driven activity, students step into the role of analysts helping the school cafeteria decide what meals to serve.
They begin by analyzing a random sample of 20 student lunch preferences, calculating counts, percentages, and scaled estimates for a total school population of 300 students.
In the second half, they compare their results to three additional surveys conducted by other students—two random and one biased (conducted only among badminton players). Through this comparison, students explore how randomness and sample size affect the reliability of conclusions.
Storyline:
The school cafeteria is planning to update its lunch menu—but instead of guessing what students want, they’ve asked for help from the student data team. You’re part of that team!
Since it’s not practical to ask all 300 students, the cafeteria is relying on random samples to figure out the most popular lunch options: 🍕 Pizza, 🌮 Tacos, 🍝 Pasta, and 🥗 Salad. Your job is to analyze data from a random sample and use math to help make a decision that reflects the whole school.
Students will develop critical reasoning skills as they investigate how random samples support valid conclusions and how bias or small sample sizes can distort data.
What Students Will Do:
- Analyze a random sample of 20 lunch preferences.
- Calculate frequency, percentage, and scaled estimates for a population of 300.
- Compare findings with three other student surveys:
- Two based on random sampling
- One biased survey from badminton players
- Identify trends and differences between samples.
- Reflect on how randomness and sample size affect the reliability of data
Skills and Concepts Covered:
- Drawing inferences from random samples
- Understanding population estimates
- Identifying biased vs. unbiased samples
- Evaluating how sample size affects results
- Interpreting data in tables and percentages
Learning Objective
Students will analyze data from random samples to estimate population characteristics, calculate proportions, and understand how sample size and sampling methods affect the reliability of conclusions. They will also evaluate biased samples and explain the importance of using sufficiently large and random samples when making inferences about a population.
Randomization Available
This worksheet supports randomization. Each student receives a different set of 20 survey responses. This fosters individualized learning and prevents of copying of answers.
💡 Tip: When assigning this activity to your classroom, you can optionally enable randomization to give each student a unique version of the problems. When you re-assign the same worksheet, each student will get a new set of questions, helping them master the content through repeated practice.
