A collection of applets addressing data analysis, sampling distribution simulations, and probability and inference. Some can be used individually, though others require context from the textbook.
Java is required. Applets work well with Firefox and Internet Explorer.
Content Quality Concerns:
Unless those who come to this collection have some familiarity with other work by Rossman and Chance (e.g., "Workshop Statistics" or "Investigating Statistical Concepts, Applications, and Methods"), they may not understand just how to work with the applets or how they can be used in the context of larger activities. Once nice new addition to the collection--for some applets (e.g., the Normal Probability Calculator)--is the inclusion of instructions for how to use the applet and a short video showing how to use the applet. It would be nice if other applets had this feature as well. The applet collection is currently undergoing revision (as the authors note on the homepage), and so this concern might eventually be addressed. Even adding a short disclaimer to the homepage to inform interested individuals that more information about using the applets can be found by consulting other resources (like "Workshop Statistics") would be helpful. Uses pi instead of p for the population proportion, but this notation is used in many (not all) books.
Content Quality Strengths:
This collection includes more than enough material, and quite a few of the topics covered in the introductory statistics course can be found in this extensive applet collection. There are engaging graphics included in many of the applets (like the Random Babies applet and the Reese's Pieces applet) and the collection is well organized. The absence of instructions for some of these applets could make it easier and more graphically pleasing to use these applets as labs and lectures. The instructor can think of creative ways to use these applets without being limited by instructions.
Ease of Use Concerns:
As mentioned earlier, the only concern is that it's not always obvious how to use each applet without background knowledge gained from "Workshop Statistics." However, since the applet collection is always undergoing revisions (and since more and more applets are added on a regular basis), this issue may soon be addressed.
Ease of Use Strengths:
Many of the applets are very easy to use and can be figured out without a lot of direction. Several of the applets include engaging visuals and vivid colors, and all of the applets are interactive. This collection is a model of high design quality. The data analysis applets are particularly strong and include good step-by-step instructions and thought-questions for the students. The probability applets are easier to understand without instructions.
Potential Effectiveness Concerns:
The instructor will need to explain the concepts and relationships between the concepts to the students. The instructor will need to write instructions for their own students. It would help the instructor to read the applicable sections of Workshop Statistics to learn what the author intended first.
Potential Effectiveness Strengths:
I regularly use this collection in my own courses to help students better grasp complex ideas and concepts. Many of the topics that students in an introductory statistics course struggle with (e.g., sampling distributions, inference)are presented in this collection, and certainly, a goal of the collection is to better help students develop a more conceptual understanding of these topics. Those interested in using this collection can find activities related to different applets in some of the other work done by Rossman and Chance (like "Workshop Statistics" and "Investigating Statistical Concepts, Applications, or Methods"). However, even without access to these resources, it would be relatively easy to create assignments and assessments based on many of the applets. By using these applets, students can discover patterns in data that might not be otherwise seen (e.g., some applets allow students to simulate taking thousands of different samples, and this can help them better see what shape a sampling distribution will take on and how sample size affects the shape of the sampling distribution).
Potential Effectiveness Rating:
Source Code Available:
Source Code Available
Free for All