5.2 Category 2 Variable 2: Naturalized U.S citizen

[Map]

popupLabels_naturalized <- paste0("<b>",countyGIS_map$name," (",countyGIS_map$FIPS,")</b>",
                    "<br><font color='",countyGIS_map$FontColorWinner,"'>",countyGIS_map$winner, 
                    ": ",
                    format(countyGIS_map$pctWinner*100,digits=4, trim=TRUE),
                    "%</font>",
                    "<br>Total votes: ", format(countyGIS_map$totalVotes,big.mark=",", trim=TRUE),
                    "<br>Percent Naturalized: ", format(round(countyGIS_map$pct_us_naturalized, 2),big.mark=",", trim=TRUE),
                    "%</font>"
                    ) %>% 
              lapply(htmltools::HTML)

pal2 <- colorNumeric(
  palette = colorRampPalette(c('red', 'white'))(length(countyGIS_map$pct_us_naturalized)), 
  domain = countyGIS_map$pct_us_naturalized, reverse=TRUE)

leaflet(countyGIS_map, options = leafletOptions(crsClass = "L.CRS.EPSG3857"), width="100%") %>%
  addPolygons(weight = 0.5, color = "gray", opacity = 0.7,
    fillColor = ~pal2(pct_us_naturalized), fillOpacity = 1, smoothFactor = 0.5,
    label = popupLabels_naturalized,
    labelOptions = labelOptions(direction = "auto")) %>%
    addPolygons(data = stateGIS,fill = FALSE,color="black",weight = 1) %>%
    addLegend(pal = pal2,values = ~countyGIS_map$pct_us_naturalized, opacity = 0.7, title = "% Naturalized",position = "bottomright")

[Scatter plot]

ggplot(countyGIS_stat, aes(pct_us_naturalized, pctGOP)) + geom_point(aes(alpha = pct_white, shape = ".")) + geom_smooth(method = "lm", se = FALSE) 

[Regression]

# Estimate regression model
pct_us_naturalized_reg <- lm(pctGOP ~ pct_us_naturalized, data=countyGIS_stat)

# Display model results
pander(summary(pct_us_naturalized_reg))

	Estimate	Std. Error	t value	Pr(>|t|)
(Intercept)	0.7199	0.00326	220.9	0
pct_us_naturalized	-0.02799	0.0009847	-28.43	4.704e-158

Fitting linear model: pctGOP ~ pct_us_naturalized

Observations	Residual Std. Error	\(R^2\)	Adjusted \(R^2\)
3083	0.1435	0.2078	0.2075