Roger Woodard

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Materials Contributed through SERC-hosted Projects

Activities (8)

Using an Applet to Demonstrate Confidence Intervals part of CAUSE Teaching Methods:Teaching with Data Simulations:Examples
Students work individually with an applet to enhance their understanding of confidence intervals. Using a detailed step by step activity, they will use simulated data from the applet to determine the percentage of confidence intervals that capture the population proportion.

Using an Applet to Demonstrate the Sampling Distribution of an F-statistic part of CAUSE Teaching Methods: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. The applet samples from six treatment populations based on user defined parameters and records by means of histogram: mean square treatment, mean square error and their ratio. 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.

Investigating the Modernity of the University Library part of CAUSE Teaching Methods:Campus-Based Learning:Examples
This activity makes use of a campus-based resource to develop a "capstone" project for a survey sampling course. Students work in small groups and use a complex sampling design to estimate the number of new books in the university library given a budget for data collection. They will conduct a pilot study using some of their budget, receive feedback from the instructor, then complete data collection and write a final report.

Influence of Outliers on Correlation part of CAUSE Teaching Methods:Teaching with Data Simulations:Examples
This activity begins with an instructor demonstration followed by a student out-of-class assignment. 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. This activity will show exactly how outliers numerically change the correlation coefficient value and to what degree.

Using an Applet to Demonstrate a Sampling Distribution part of CAUSE Teaching Methods:Interactive Lectures:Examples
This in-class demonstration combines real world data collection with the use of the applet to enhance the understanding of sampling distribution. Students will work in groups to determine the average date of their 30 coins. In turn, they will report their mean to the instructor, who will record these. The instructor can then create a histogram based on their sample means and explain that they have created a sampling distribution. Afterwards, the applet can be used to demonstrate properties of the sampling distribution. The idea here is that students will remember what they physically did to create the histogram and, therefore, have a better understanding of sampling distributions.

Using an Applet to Demonstrate Sampling Distributions of Regression Coefficients part of CAUSE Teaching Methods:Interactive Lectures:Examples
This visualization activity combines student data collection with the use of an applet to enhance the understanding of the distributions of slope and intercept in simple linear regression models. The applet simulates a linear regression plot and the corresponding intercept and slope histograms. The program allows the user to change settings such as slope, standard deviation, sample size, and more. Students will then see theoretical distributions of the slope and intercept and how they compare to the histograms generated by the simulated linear regression lines.

Correlation Guessing Game part of CAUSE Teaching Methods:Games:Examples
In this game activity, students match correlation values with plots generated by the applet. Competition in this game setting encourages students to become more involved in the classroom and attainment of learning objectives. This game is best if used in a lab setting, although it may be modified to fit other classroom situations.

Interpreting Graphical Displays of Univariate Distributions part of CAUSE Teaching Methods:Gallery Walks:Examples
Working in groups, students provide practical interpretations of graphs, considering shape, center, and spread. Each group posts their interpretation for one graph and critiques other groups' interpretations on other graphs. Students examine key aspects (shape, spread, location, etc) of histograms and stem plots to develop the ability to interpret graphics. This activity gets the students up and out of their seats and working together. It is a good activity for early in a term. The Gallery Walk idea can be adapted for different sized classes but this activity has been designed for classes up to 65 students.