--- title: "Lecture 10 Exercises" author: "Your Name" output: html_document --- ```{r setup, message = FALSE, warning = FALSE, echo=FALSE} knitr::opts_chunk$set(message = FALSE, warning = FALSE, dev="svg", tidy=TRUE, tidy.opts = list(only.comment=TRUE, width.cutoff=80)) library(summarytools) library(dplyr) ``` We're going back to the COVID-19 data that we used before, we need to load it first. (It's also available locally in the RStudio.cloud instance or from [my website](https://quantoid.net/files/reg3/counties.rda)) ```{r} load(file("https://quantoid.net/files/reg3/counties.rda")) ``` This makes an object in your workspace called `counties`. To remind, here's a summary of the data: ```{r, results='asis', eval=FALSE} counties %>% select(-c("fips", "NAME", "date", "state", "st")) %>% dfSummary(., plain.ascii=FALSE) ``` I want you to use the data to answer the following questions. ### Question 1 Choose a few continuous variables as predictors of the log of `cases` per capita and estimate a linear model. - Use smoothing splines to replace the splines in your previous exercise. If you like, you could use a subset of one state's data. - Use tests of the same parametric form as in your previous exercises.