--- title: "Lecture 4 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 to use data from the sixth wave of the World Values Survey, 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/wvs.rda)) ```{r} load(file("https://quantoid.net/files/reg3/wvs.rda")) ``` This makes an object in your workspace called `counties`. To remind, here's a summary of the data: ```{r, results='asis'} wvs %>% select(-c(1,2)) %>% dfSummary(., plain.ascii=FALSE) ``` I want you to use the data to answer the following questions. ### Question 1 Figure out whether the `income` variable (which is income steps) could be used as a quantitative variable to predict `emancip_values`. Use some other controls in your model. - Test whether the model treating `income` as categorical is better. - Plot the results to see *how* non-linear they are. ### Question 2 Now, we want to put subjective perceptions of class (the `class` variable) on the left-hand side of the equation. Pick a few variables that you think might influence someone's self-perceived class. - Use the `alsosDV()` function to see whether it behaves linearly relative to the variables on the RHS of the model. - Plot the measurement function. - What would you do if this were your project?