Selecting variables for a linear model is dicey. Let's get started! If this vid helps you, please help me a tiny bit by mashing that 'like' button. For more #rstats joy, crush that 'subscribe' button!
I heard you mention this wouldn't be devoted to inference, but wondered if you could help me understand the pitfalls of stepwise elimination as its summarized in this sentence I found: "If you remove the insignificant terms and then refit, the inference results (p-values) would not include the "effect" of the previous selection". I can't wrap my head around what this means practically and what the implications might be. Any corrections or thoughts? Thank you, I really enjoy your videos!
Hi! Yes, that's a reasonable way of describing it. As a result of the process used to get them, the p-values of the remaining terms will be low after variable selection. You shouldn't use their lowness to draw conclusions about statistical significance.
My humble request you to make videos regarding ggplot2 with tools geom_ point, geom_bar, geom_line, pie chart, geom_area and others geom relates charts with one single dataset with every charts all the syntax. It will be useful as a beginner. Thank you so much for your great effort. ❤❤❤❤
Hi! I've got vids on most of those geoms, including point (ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE--k5pvxyyi8o.html) and bar (ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-HvOQFQzIg5c.html). You might also be interested in my ggplot overview (ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-McL9MMwmIZY.html), which covers a lot of geoms using only a few data sets.