diff --git a/.DS_Store b/.DS_Store
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diff --git a/.gitignore b/.gitignore
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+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
diff --git a/AgetoSalary.txt b/AgetoSalary.txt
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+Age	Salary
+25	45663.9
+35	68831.49
+45	78679.09
+55	75324.28
+65	68826.28
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diff --git a/Exercise09-HunterGonzalez.R b/Exercise09-HunterGonzalez.R
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+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
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diff --git a/Exercise09.Rproj b/Exercise09.Rproj
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+
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+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
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+UseSpacesForTab: Yes
+NumSpacesForTab: 2
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+
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+LaTeX: pdfLaTeX