# Activities

# Subject: Statistics

# Pedagogy

- Campus-Based Learning 1 match
- Cooperative Learning 7 matches
- Gallery Walk 1 match
- Games 1 match
- Interactive Lectures 6 matches
- Lecture 6 matches
- Making and Testing Conjectures 6 matches
- Quantitative Reasoning 6 matches
- Quantitative Skills 6 matches
- Simulation of Data 7 matches
- Teaching with Data 7 matches
- Teaching with Models 5 matches

Results 1 - 10 of **34 matches**

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.

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.

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

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.

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.

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)

Influence of Outliers on Correlation part of Teaching with Data Simulations:Examples

In this visualization activity, students will observe their instructor create a scatterplot and observe how the correlation coefficient changes when outlier points are added. Students are then given a follow up assignment which guides them through the applet. In addition, the assignment provides insight about outliers and their effect on correlation.

Coke vs. Pepsi Taste Test: Experiments and Inference about Cause part of Teaching with Data Simulations:Examples

The Coke vs. Pepsi Taste Test Challenge has students design and carry out an experiment to determine whether or not students are able to correctly identify two brands of cola in a blind taste test. In the first ...

Reese's Pieces Activity: Sampling from a Population part of Teaching with Data Simulations:Examples

This activity uses simulation to help students understand sampling variability and reason about whether a particular samples result is unusual, given a particular hypothesis. By using first candies, then a web applet, and varying sample size, students learn that larger samples give more stable and better estimates of a population parameter and develop an appreciation for factors affecting sampling variability.

Simulating Size and Power Using a 10-Sided Die part of Teaching with Data Simulations:Examples

This group activity illustrates the concepts of size and power of a test through simulation. Students simulate binomial data by repeatedly rolling a ten-sided die, and they use their simulated data to estimate the size of a binomial test.