I will be covering Topic 70: Two-Way Analysis of Variance within this presentation. This is an important topic for understanding the benefits of employing multiple classification variables.
The first part of my presentation examines the importance of analyzing the significance of the main effects that can be garnered from the mean values of a study. Understanding how to frame these main effects and analyzing the mean values from a study are two paramount factors for employing Two-Way ANOVA. This can allow for interactions between two different classifications to be examined in a measurable manner.
The tail end of my presentation further delves into interactions that can occur in Two-Way ANOVA. This section places an emphasis on understanding how measuring the significance of the main effects is important, but interactions can occur between classification despite levels of main effect significance. The insight gained from these interactions is the main benefit of employing Two-Way ANOVA over Single-Way ANOVA.
A YouTube video of my presentation is embedded below, but I have also listed a hyperlink in case the Mini Player malfunctions.
Good day Cody. Your presentation was totally informational. I thought you did a excellent job of explaining the process One way and Two nova test. Your narration was pleasant and match your examples of variables between male and female regarding data output. These test such as A-nova and T-Test are both important to stat and probability questions regarding social science. I also thought you did an exceptional job covering of the topic with your examples and explaining the importance of why the test are needed and utilized.