# Examples of Testing Conjectures

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Seeing and Describing the Predictable Pattern: The Central Limit Theorem part of 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 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 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 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 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 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.