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 airlines flying out of the same city. They first identify measures that can be used to compare the two airlines. Working in small groups, the students decide the size of a meaningful difference between the airlines for each measure and use that information to determine a rule that for deciding if one airline is more reliable than another. The students apply their rule to flight arrival delay data for the two airlines from four additional departure cities, and use the results to write a report to the magazine editor on whether or not one airline is more reliable than the other. This activity can serve as an introduction to ideas of central tendency and variability, and prepares students for formal approaches to comparing groups.

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 given samples of SPAM and non-SPAM subject lines to examine. After their rules are ready, they are given a test set of data to use and are asked to come up with a numerical measure to quantify how well their method (model) works. Each team writes a report describing how their model works and how well it performed on the test data. This activity could serve as an introduction to ideas of classification. Alternatively, the activity could be the basis for student introduction to types of statistical errors.

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 to develop the model. Students write a report to the crime victim that identifies a suspect and justifies their decision. The activity sets the stage for students to learn about regression models, and reinforces their understanding of central tendency and variability. It is suggested that this activity be used prior to a formal introduction to linear relationships.

This model-eliciting activity (MEA) challenges students to develop ideas about center and variability when making decisions based on data. Students examine data on departure delays for five airlines flying out of the Chicago O'Hare airport. The task is to develop a model to determine which airline has the best chance of departing on time. Students write a report that identifies the best airline and the reasoning behind their decision.

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 intuitions about random events and randomly generated data are often incorrect or misleading, this activity initially focuses students' attention on describing characteristics of 25 playlists that were randomly generated. Students then use these characteristics to come up with rules for judging whether a playlist does NOT appear to be randomly generated. Students test and revise their rules (model) using five additional playlsits. Then, they apply their model to three particular playlists that have been submitted to Apple by an unhappy iPod owner who claims the shuffle feature on his iPod is not generating random playlists. In the final part of the activity, students write a letter to the ipod owner, on behalf of Apple, explaining the use of their model and their final conclusion about whether these three suspicious playlists appear to have been randomly generated.This lesson provides an introduction to the fundamental ideas of randomness, random sequences and random samples.

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 a sample of data that includes multiple flights of paper airplanes by three different pilots. Each team writes a report describing how their judging scheme can be implemented by the judges of the contest. This activity could serve as an introduction to ideas of central tendency and variability. It can also set the stage for understanding the correspondence between data sets and their graphical representations. Alternatively, the activity could be the basis for student introduction to analysis of variance.

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 given a set of data for a few students and asked to use their scores to determine an index of study effectiveness. After determining a method, they are then asked to use this index to put five students in rank order according to their scores on study effectiveness. Students write a report explaining the method they used to determine these scores and how they produced their ratings.