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Emerging statisticians develop the ability to make inferences from sample data while also working on proportional relationships in general. Here, young learners examine samples for bias, and then use random samples to make inferences for larger populations. Engaging situations and realistic (but not overly complicated) numbers combine seamlessly here with the spiraled review of solving equations with common denominators.
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CCSS:
Designed
Concepts
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Instructional Ideas
- Learners might create their own biased and representative samples, then trade with one another
- Split the class in thirds, and have each third work the problems in one of the methods from the lesson. Then compare results and switch methods
Classroom Considerations
- Limited number of examples for practice and explanation, remediation or skill practice might require finding other data sets
- Activity and exit ticket have student printouts, but lesson examples and problems do not (but could be easily copy-pasted from teacher notes)
Pros
- Presentation of statistics without use of complicated lingo or lecture makes a potentially complicated topic very approachable
- Class group work on the scenarios leads to a deep understanding of representative samples
- Multiple methods for working each problem lend themselves well to different learning styles
Cons
- No answer key for group work (categorizing scenarios)
- No teaching notes for developing equations from word problems in examples