The portion bolded below is the response to this discussion post. Can you help me craft a responsible but brief response?

In many ways, comparing multiple sample means is simply an extension of what we covered last week. Just as we had 3 versions of the t-test (1 sample, 2 sample (with and without equal variance), and paired; we have several versions of ANOVA single factor, factorial (called 2-factor with replication in Excel), and within-subjects (2-factor without replication in Excel). What examples (professional, personal, social) can you provide on when we might use each type? What would be the appropriate hypotheses statements for each example?

Well on my job we have to keep up with when we pickup/drop-off members and the miles it takes to get there. With this you could compare the time od pickups/drop-offs to the miles and this would make for a ANOVA single factor. As we all know with each test you're comparing the differences to get results. According to Tanner & Youssef-Morgan, "Factorial ANOVA describes an analysis of variance with more than one IV" (Tanner & Youssef-Morgan, 2013). Example using social media; I could compare the number of friends I started with to how many I actually have now. ANOVA within subjects you have to subtract between the groups you're comparing.