Overview
When we want information about the population proportion \(p\) of successes, we often take a simple random sample and use the sample proportion \(\hat p\) to estimate the unknown parameter \(p\). The sampling distribution of the sample proportion \(\hat p\) describes how the statistic varies in all possible samples of the same size from the population. In this lesson, students will explore the shape and variability of this distribution, and learn how to evaluate claims using the sampling distribution.
Underlying Pages
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0. Student Directions -
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1. A quick review... -
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2. Assessing Normality -
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3. Investigating Normal Probability Plots using CODAP -
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4. When is the sampling distribution Normal(ish)? -
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5. Putting it all together! -
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Standards
Computational Thinking in STEM 2.0
- Computational Data Practices
- Computational Modeling and Simulation Practices