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Pedagogy

showing only Making and Testing Conjectures Show all Pedagogy

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Seeing and Describing the Predictable Pattern: The Central Limit Theorem part of Testing Conjectures:Examples
This activity helps students develop a better understanding and stronger reasoning skills about the Central Limit Theorem and normal distributions. Key words: Sample, Normal Distribution, Model, Distribution, Variability, Central Limit Theorem (CLT)

Reasoning About Center and Spread: How do Students Spend Their Time? part of Testing Conjectures:Examples
This activity helps students develop better understanding and stronger reasoning skills about distributions in terms of center and spread. Key words: center, spread, distribution

Independent Samples t-Test: Chips Ahoy® vs. Supermarket Brand part of Testing Conjectures:Examples
In this hands-on activity, students count the number of chips in cookies in order to carry out an independent samples t-test to compare Chips Ahoy® cookies and a supermarket brand. It can involve discussion of randomness and independence of samples, comparing two parameters with null and alternative hypotheses, and the practical issues of counting chips in a cookie.

Using Your Hair to Understand Descriptive Statistics part of Testing Conjectures:Examples
The purpose of this activity is to enhance students’ understanding of various descriptive measures in statistics. In particular, students will gain a visual understanding of means, medians, quartiles, and boxplots without doing any computations by completing this activity.

A ducks story- introducing the idea of testing (statistical) hypotheses part of Testing Conjectures:Examples
The ideas and vocabulary of testing statistical hypotheses, from research question to conclusion, are introduced using a simple story regarding a population proportion and a small sample using the binomial table to find the p-value.

An In-Class Experiment to Estimate Binomial Probabilities part of Testing Conjectures:Examples
This hands-on activity asks students to conduct a binomial experiment and calculate a confidence interval for the true probabiity. It is useful for involving students, and for having a discussion about the interpretation of confidence intervals and the role of sample size in estimation.