Hunter Gonzalez- Solutions to Exercise09

.gitignore

@@ -0,0 +1,4 @@
+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata

AgetoSalary.txt

@@ -0,0 +1,6 @@
+Age	Salary
+25	45663.9
+35	68831.49
+45	78679.09
+55	75324.28
+65	68826.28

Exercise09-HunterGonzalez.R

@@ -0,0 +1,23 @@
+library(ggplot2)
+#Question1
+averagesalary<-read.table("AgetoSalary.txt",header=TRUE,sep="\t",stringsAsFactors=FALSE)
+ggplot(data = averagesalary, aes(x=Age,y=Salary))+
+  geom_point()+
+  stat_smooth(method="lm")
+  theme_classic()
+#Question2
+data=read.table("data.txt",header=TRUE,sep=",",stringsAsFactors=FALSE)
+## Barplot of the means of the two populations
+ggplot(data, aes(x=region, y=observations, fill=as.factor(region))) +
+  stat_summary(geom="bar", fun="mean") +
+  xlab("Regions") +
+  ylab("Average # of Observations")+
+  theme_bw()
+
+##Scatterplot of all of the observations
+ggplot(data = data, aes(x=region, y=observations))+
+  geom_point() +
+  geom_jitter()+
+  theme_bw()
+#Stories of the Scatterplot vs Bar Plot: The bar plot makes it seem like there are a fairly similar amount of average observations, but the 
+# scatter plot shows that there are vastly different distributions for the observations in different regions

Exercise09.Rproj

@@ -0,0 +1,13 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX