#Data Sceince Homework $7$ Fall $2024$

data $<-$ read.csv$("$storms$.$csv$")$

ggplot$($data$,$ aes$($x $=$ year$))+$

$$geom$\_$bar$($stat $=$ "count"$)$

ggplot$($data$,$ aes$($x $=$ year, fill $=$ factor$($Type$)))+$

$$geom$\_$bar$($stat $=$ "count"$)+$

$$scale$\_$fill$\_$discrete$($

$$name $=$ "Type of Hurricane",

$$labels $=$ c$("$Tropical Storm", $"1","2","3","4","5")$

$)$

data$\_$table $<-$ table$($data$Type$)$

data$\_$table

data$Type$\_$New $<-$ ifelse$($test $=$ data$type$1==0,$ yes $=0,$ no $=1)$

table$($data$Type$\_$New$)$

options$($viewer $=$ NULL$)$

library$($leaflet$)$

m $<-$ leaflet$()$

m $<-$ addTiles$($m$)$

m $<-$ addProviderTiles$($m$,$ "Esri.OceanBasemap"$)$

cols $<-$ c$("$red$",$ "navy"$)$

m $<-$ addCircleMarkers$($m$,$

$$lng $=$ data$lon,

$$lat $=$ data$lat,

$$radius $=2\mathrm{.}5,$

$$color $=$ cols$[$data$Type$\_$New $+1],$

$$popup $=$ paste$("$Year:$",$ as$.$character$($data$Year$))$

$)$

m $<-$ addLegend$($m$,$

$$ "topright",

$$ colors $=$ cols,

$$ labels $=$ c$("$tropical$",$ "non$-$tropical"$),$

$$ title $=$ "Type of Hurricane",

$$ opacity $=1$

$)$

m

log$\_$model $<-$ glm$($Type$\_$New ~ data$lat, data $=$ data, family $=$ "binomial"$)$

summary$($log$\_$model$)$

summary$($log$\_$model$)$$coefficients

exp$($coefficients$($log$\_$model$)[2])$

confint.default$($log$\_$model$)[2,]$

exp$($confint$.$default$($log$\_$model$)[2,])$

predict$($log$\_$model, newdata $=$ list$($lat $=$ c$(10,23\mathrm{.}5,30)),$ type $=$ "response"$)$

lats $<-$ seq$($min$($data$lat$),$ max$($data$lat$),0\mathrm{.}1)$

probs $<-$ predict$($log$\_$model,

$$ newdata $=$ data.frame$($lat $=$ lats$),$

$$ type $=$ "response",

$$ se$.$fit $=$ TRUE

$)$

pm $<-$ probs$fit

pu $<-$ probs$fit $+$ probs$se$.$fit $*1\mathrm{.}96$ # $95\%$ confidence interval

pl $<-$ probs$fit $-$ probs$se$.$fit $*1\mathrm{.}96$ # $95\%$ confidence interval

plot$($data$lat,

$$ data$Type$\_$new,

$$ pch $=16,$

$$ cex $=1,$

$$ ylab $=$ "Probability",

$$ xlab $=$ "Formation Latitude $($N$)"$

$)$

grid$()$

polygon$($c$($rev$($lats$),$ lats$),$ c$($rev$($pl$),$ pu$),$

$$col $=$ "grey$90",$ border $=$ NA

$)$

lines$($lats$,$ pm$,$ lwd $=2)$

lines$($lats$,$ pu$,$ lwd $=2,$ col $=$ "red"$)$

lines$($lats$,$ pl$,$ lwd $=2,$ col $=$ "red"$)$

abline$($h $=0\mathrm{.}1,$ lty $=2)$

abline$($h $=0\mathrm{.}5,$ lty $=2)$

abline$($h $=0\mathrm{.}9,$ lty $=2)$

Above is the $$original R code hurricane data set.$$Provide a$$five$-$page Report with images$$on recreating hurricane research using the new dataset, The report include the map or the logistic regression graph, and provide a$$R code file$$for data cleaning, map and logistic regression graph.$$Ensure code is accurate and thoroughly tested.