Choose one of David Robinson’s tidytuesday screencasts, watch the video, and summarise. https://www.youtube.com/channel/UCeiiqmVK07qhY-wvg3IZiZQ
Tidy Tuesday screencast: analyzing franchise revenue
July 22nd, 2019
Hint: What’s the source of the data; what does the row represent; how many observations?; what are the variables; and what do they mean?
“Franchises” is the group, similar to what we often use as CarData or mosaicData. The x axis is total revenue, and that is whats being examind from the franchises throughout every graph/plot made. ## Q4-Q5 Describe how Dave approached the analysis each step. Hint: For example, importing data, understanding the data, data exploration, etc.
He examined the data live, which set up for some surprises throughout the video. When he imported the data, he briefly explain what data was going to be analzyed; and when he talked about understanding the analysis, he then explained what we as watchers shoiuld be looking for and then therefore ## Q6 Did you see anything in the video that you learned in class? Discuss in a short paragraph.
Yeah, one very basic thing we learned in class that is demonstrated in Daves video is the creation of basic ggplots, as he does that in the very beginning; and then the scatterplot which we have covered on how to create completely. Everything else was rather complex.
That based on the scatterplot, there are like one hundred times more franchises being created in modern times rather than the 1950s and before.
I thought it was pretty cool to see that based of the scatterplot, franchises developed earlier tended to become more successful in terms of total revenue. This then made me realize it made sense tho because it has had a lot longer to grow.