Comparing Two Airlines part of Inventing and Testing Models:Examples
In this model‐eliciting activity (MEA), students are hired by a travel magazine to determine if two airlines that fly into Chicago are equally reliable. They examine data of flight arrival delay times for both ...

Judging Randomness part of Inventing and Testing Models:Examples
This model-eliciting activity has students create rules to allow them to judge whether or not the shuffle feature on a particular iPod appears to produce randomly generated playlists. Because people's ...

Measuring Study Effectiveness part of Inventing and Testing Models:Examples
This model-eliciting activity challenges students to operationally define a construct (study effectiveness). Students are given a survey to review that rates different aspects of study behaviors. They are then ...

Identifying a Theft Suspect part of Inventing and Testing Models:Examples
This model-eliciting activity (MEA) challenges students to develop a model for predicting the characteristics of a person who has committed a crime. Students work with real data on shoe length, height, and gender ...

Creating a Spam Filter part of Inventing and Testing Models:Examples
This activity asks students to work in a team to develop a set of rules that can be used to program a SPAM filter for a client. The rules are based on characteristics of the subject lines of emails. Students are ...

Judging a Paper Airplane Contest part of Inventing and Testing Models:Examples
This model-eliciting activity has students determine how to create a fair judging scheme for a paper airplane contest while considering both the most accurate paper airplane and the best floater. Students are given ...

Using an Applet to Demonstrate Confidence Intervals part of Teaching with Data Simulations:Examples
Students will utilize an applet to further expand their knowledge of confidence intervals.

Using an Applet to Demonstrate the Sampling Distribution of an F-statistic part of Interactive Lectures:Examples
This visualization activity combines student data collection with the use of an applet to enhance the understanding of the distributions of mean square treatment (MST), mean square error (MSE) as well as their ratio, an F-distribution. Students will see theoretical distributions of the mean square treatment, mean square error and their ratio and how they compare to the histograms generated by the simulated data.

The Evolution of Pearson’s Correlation Coefficient/Exploring Relationships between Two Quantitative Variables part of Interactive Lectures:Examples
The evolution of ideas is often ignored in the teaching of statistics. It is important to show students how definitions and formulas evolve. This activity describes a fairly straightforward activity of how measures of association can evolve.

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.