8 Sneaky Salary Copyright © 2026 Pearson Education, Inc. Sneaky Salary (50 – 60 minutes) Learning Objective(s): ● Students will compare population and sample statistics. ● Students will compare and contrast sampling methods. ● Students will make inferences from collected data. ● Students will determine whether a graph is misleading. Material needed: ● Student pages: Sneaky Salary Lesson Procedure: Warm–Up 10 minutes Prompt: Why might someone use statistics to mislead people? Discuss: statistics, surveys Guided Instruction 15 minutes Present: scenario for Sneaky Salary. Example: Someone conducts a survey to determine the average height of everyone in a town. They have no way of gathering this information from every person. How do they make sure that the sample of people they survey represents the population as accurately as possible? Discuss how simple random, stratified, cluster, and systematic sampling methods work. Discuss how convenience, judgment, and quota methods may not lead to valid results. Review: key terms – population statistic, sample statistic, sampling methods population parameter: a numerical value that describes an entire population’s characteristic. sample statistic: a numerical value that describes a sample of the data. sampling methods: the specific techniques used to select individuals from a larger population for a study. Independent Practice 20 minutes Distribute: student activity Sneaky Salary Allow students to work individually or in pairs. Remind students to be courteous and appropriate in their speaking and writing. Tell students to support each other as they approach the questions. Closure 10–15 minutes Review Answers: 1. a. sample statistic; b. No. The sample was not randomly selected, and it was only from one part of the city. 2. The convenience sampling method was used. This may not accurately represent the population; it is not random and is from one area in the city. 3. Salaries in this city have an even distribution. Slightly fewer people have salaries over $180,000 than the other three ranges. 4. a. Simple random would have randomly selected participants from throughout the whole city, which would reflect the population better. b. Stratified would have made sure that participants from various subgroups in the city were all included, instead of being likely to leave out some groups of people. c. Cluster would have divided the city randomly into clusters, and one of the clusters, which would represent the population better, would be chosen. d. Systematic sampling would have allowed for more randomness by selecting random participants based on number. 5. Because the y-axis begins at 40, the last bar appears to be close to 0, when in reality it is quite close to the heights of the other bars. 6. The newspaper might be trying to show that there are not many people in the city with large salaries. Discuss: What statistics have you seen that may be misleading? How are they misleading?
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