This 9 min 20 sec YouTube video (part of a series) explains the basic ideas behind ANOVA and the F test statistic.
Type of Material:
Tutorial
Recommended Uses:
It seems like this would be used as a supplemental resource for students, outside of the classroom. It might be a good reference for students who want to understand ANOVA beyond what they are exposed to in the classroom or in their required textbook.
Technical Requirements:
Access to an Internet browser. Audio capability is helpful, but the video is closed-captioned.
Identify Major Learning Goals:
To understand the theoretical basics of ANOVA. To understand the different parts of the F-statistics within the context of the one-way between-subjects ANOVA (i.e., understanding between-groups and within-groups variance and how the magnitude of each affects the size of the F-statistic). To understand why ANOVA is used versus multiple t-tests.
Target Student Population:
Advanced high-school students, college-level students who are studying ANOVA. Students more advanced than just introductory level.
Prerequisite Knowledge or Skills:
An understanding of inference and many of the terms studied in a unit on inference (e.g., null and alternative hypothesis, p-values, test statistics, sampling variability, statistical significance). An understanding of the two-sample t-test.
Content Quality
Rating:
Strengths:
The video nicely lays out what the F-statistic and shows how between and within groups variability will affect the magnitude of the F-statistic. The video includes graphs to show viewers how overlap between our populations can affect the magnitude of the F-statistic. There is also nice discussion about the reason for using ANOVA rather than multiple t-tests. Having subtitles in the video is also a nice touch.
Concerns:
Without viewing Part A of this presentation (which the author links to at the beginning of the video), it's very difficult to follow the ideas behind the experiment that is mentioned often in this video. Also, I wish time had been spent trying to discuss the concept of practical significant. Just because we get a large F-statistic does not mean the results are meaningful. It could be due to a very large sample size.
I teach my students to use a 2-sample comparison of means if only 2 groups are being compared and to use one-way ANOVA if more than 2 groups are being compared. This lecture focuses on using ANOVA for comparing 2 groups. He does explain that the independent t test can also be used if you only have 2 groups, but he doesn’t say why you would choose one type of test over another type. It would have been nice to see the hypotheses stated, too. I realize this is Part B, but it would have been good to see them restated.
Potential Effectiveness as a Teaching Tool
Rating:
Strengths:
This is a basic, straightforward explanation of the variance involved in ANOVA. Powerpoints and several pictures are used to explain the concepts. I feel the video covers an important topic and moves in the right direction in terms of attempting to do this with graphics. I can see something like this being a good outside of class reference for students.
Concerns:
The students don’t have to put in any effort for this. They are being talked to, but they don’t have to think, and they’re not being shown anything they couldn’t see in their lecture classroom.
Ease of Use for Both Students and Faculty
Rating:
Strengths:
I like that this video moves along quickly and doesn't just present slides cluttered with text and no graphics. I especially liked the slides in which some color was added. The narrator has a calm voice that is easy to listen to, and the narration is very clear. It was a nice touch to add information about the beginning of the video about how to turn off closed-captioning since this can sometimes obscure what is being presented on the screen.
I also like that the author gives the link to Part A.
Concerns:
I felt that adding more animations could engage the viewer more. The video is not terribly interactive.
Creative Commons:
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