Class Instructions for 3/29/2017 - Regression

032292017.txt

## RUN ALL THIS SYNTAX BEFORE WE START
## This will install and load all the packages you need for class today. 

ipak <- function(pkg){
    new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
    if (length(new.pkg)) 
        install.packages(new.pkg, dependencies = TRUE)
    sapply(pkg, require, character.only = TRUE)
}

packages <- c("ggplot2", "dplyr", "car", "highcharter", "ggcorrplot", "dwplot")
ipak(packages)

## STOP AND WAIT
## Take a look at this dataset
## Here's the data link: 
df <- read.csv(url("https://raw.githubusercontent.com/ryanburge/pls2003_sp17/master/living.csv"))

## Let's start by finding comparing height and weight again.  
## Now we need to start adding variables for control purposes. 

## Let's talk about the logic of regression analysis. 
## Let's visualize it. 
## Here's the syntax for a regression

reg1 <- lm(DV ~ IV + IV + IV + IT, data = NAME OF THE DATASET)
summary(reg1)


dwplot(reg1)  + geom_vline(xintercept = 0, colour = "grey50", linetype = 2)

### P-Hacking!!
https://fivethirtyeight.com/features/science-isnt-broken/#part1


Here's the data link: 
simon <- read.csv(url("http://goo.gl/exQA14"))

Here's the link to the codebook: 
http://opensiuc.lib.siu.edu/cgi/viewcontent.cgi?article=1010&context=ppi_statepolls