---
title: "Q's Regression Code"
output:
  word_document: default
  html_notebook: default
---

```{r}
install.packages("pastecs")
install.packages("corrplot")
```

```{r}
library(pastecs)
library(corrplot)
```

```{r}
DATA <- read.csv("/Users/Q/Desktop/adjDATA.csv")
DATA
```

```{r}
options(scipen = 999)
```

```{r}
stat.desc(DATA)
```

```{r}
regout <- lm(DATA$GUNDEATHS ~ DATA$NICS + DATA$INCOME + DATA$ED + DATA$PDUM)
regout
```

```{r}
GLS <- lm(DATA$GUNDEATHS ~ DATA$NICS/DATA$POP + DATA$INCOME/DATA$POP + DATA$ED/DATA$POP +DATA$PDUM/DATA$POP)
summary(GLS)
```

```{r}
VIF1 <- lm(DATA$GUNDEATHS ~ DATA$NICS)
summary(VIF1)
```

```{r}
VIF2 <- lm(DATA$GUNDEATHS ~ DATA$INCOME)
summary(VIF2)
```

```{r}
VIF3 <- lm(DATA$GUNDEATHS ~ DATA$ED)
summary(VIF3)
```

```{r}
VIF4 <- lm(DATA$GUNDEATHS ~ DATA$PDUM)
summary(VIF4)
```

```{r}
summary(regout)
```

```{r}
corrs <- cor(DATA)
corrs
```

```{r}
residuals <- resid(regout)
residuals
```

```{r}
parkstats <- lm(formula = log(residuals^2) ~ log(POP), data = DATA )
parkstats
```

```{r}
summary(parkstats)
```