diff --git a/07_final_assignment/.RData b/07_final_assignment/.RData
index eb9623d..019e1f3 100644
--- a/07_final_assignment/.RData
+++ b/07_final_assignment/.RData
Binary files differ
diff --git a/07_final_assignment/baboonSimulation.R b/07_final_assignment/baboonSimulation.R
index 9d3c343..5ec19c6 100644
--- a/07_final_assignment/baboonSimulation.R
+++ b/07_final_assignment/baboonSimulation.R
@@ -524,6 +524,8 @@
   return(z)
 }
 
+data = harvest.data(TRUE)
+
 
 
 mat1 = matrix(rexp(15*15, rate=.1), ncol=15, nrow=15)
@@ -542,6 +544,58 @@
              col = topo.colors(100))
 }
 
+########################################################################################
+####                            DATA ANALYSIS
+########################################################################################
+
+#0. preprocessing
+monkeydat$GeneralAccuracy = as.numeric(monkeydat$GeneralAccuracy)
+monkeydat$WordAccuracy = as.numeric(monkeydat$WordAccuracy)
+monkeydat$NonwordAccuracy = as.numeric(monkeydat$NonwordAccuracy)
+monkeydat$NumTrials = as.numeric(monkeydat$NumTrials)
+monkeydat$NumWordsLearned = as.numeric(monkeydat$NumWordsLearned)
+monkeydat$NumNonwordsPresented = as.numeric(monkeydat$NumNonwordsPresented)
+
+
+#1. chance level
+chance.level <- r / 2
+chance.level
+
+max.accuracy <- 1-chance.level
+max.accuracy
+
+max(data$GeneralAccuracy)
+max(data$WordAccuracy)
+max(data$NonwordAccuracy)
+
+
+#2. correlations
+#interesting to look at (& to write in the paper):
+cor(data$WordAccuracy, data$NonwordAccuracy)
+cor(monkeydat$WordAccuracy, monkeydat$NonwordAccuracy)
+#why is this correlation so different???
+
+cor(data$GeneralAccuracy, data$NonwordAccuracy)
+cor(monkeydat$GeneralAccuracy, monkeydat$NonwordAccuracy)
+
+cor(data$GeneralAccuracy, data$WordAccuracy)
+cor(monkeydat$GeneralAccuracy, monkeydat$NonwordAccuracy)
+
+
+#3. linear model
+#fitting a linear model:
+m1 = lm(GeneralAccuracy ~ alpha, data=data)
+summary(m1)
+
+m2 = lm(GeneralAccuracy ~ alpha + beta, data=data)
+summary(m2)
+
+anova(m1, m2)
+
+m3 = lm(GeneralAccuracy ~ alpha * beta, data=data)
+summary(m3)
+
+anova(m2, m3)
 
 
 ########################################################################################