## Question 1 Load any required packages. Load the `voter_id_turnout` data set. Calculate mean voter turnout in states with and without strict voter ID laws using the `group_by` and `summarise`...

## Question 1
Load any required packages. Load the `voter_id_turnout` data set. Calculate mean voter turnout in states with and without strict voter ID laws using the `group_by` and `summarise` functions. Also show the difference in means (calculate this however you like; the `infer` package is one option). Show your work and results using code, then state in writing what you found.


## Answer 1


## Question 2
Is the analysis in Question 1 experimental or observational? Why?
Are there any potential sources of omitted variables bias? If so, what is one potential confound? Explain why that variable might be a confound.


## Answer 2










## Question 3
Let's assume for this question that there is no omitted variables bias present. Can we conclude based on the means alone that voter ID laws had the observed effect? Why or why not?


## Answer 3












## Question 4
Use `ggplot` to visualize the relationship between strict voter ID laws and turnout in the 2012 election.


## Answer 4












## Question 5
Use linear regression to formally test whether there is a statistically significant difference in voter turnout for states without versus states with strict voter ID laws. Show the tidied model output (produced by broom::tidy()).
Interpret the coefficient on `strict_id_law`, as well as its p-value. Be thorough when interpreting what the p-value here tells us (i.e. don't just say whether or not it is significant). What can we conclude based on these results?


## Answer 5