diff --git a/.gitignore b/.gitignore
index d70ba59..552fad7 100644
--- a/.gitignore
+++ b/.gitignore
@@ -3,3 +3,7 @@
 *.log
 *.synctex.gz
 .Rproj.user
+<<<<<<< HEAD
+=======
+.Rhistory
+>>>>>>> bd13a62b89d8db9ab6ef3a397f69c56a6a749368
diff --git a/03_rescorlawagner.Rproj b/03_rescorlawagner.Rproj
deleted file mode 100644
index 8e3c2eb..0000000
--- a/03_rescorlawagner.Rproj
+++ /dev/null
@@ -1,13 +0,0 @@
-Version: 1.0
-
-RestoreWorkspace: Default
-SaveWorkspace: Default
-AlwaysSaveHistory: Default
-
-EnableCodeIndexing: Yes
-UseSpacesForTab: Yes
-NumSpacesForTab: 2
-Encoding: UTF-8
-
-RnwWeave: Sweave
-LaTeX: pdfLaTeX
diff --git a/03_rescwag_wugniz/03_rescorlawagner.Rproj b/03_rescwag_wugniz/03_rescorlawagner.Rproj
new file mode 100644
index 0000000..8e3c2eb
--- /dev/null
+++ b/03_rescwag_wugniz/03_rescorlawagner.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
diff --git a/03_rescwag_wugniz/assignment3.Rmd b/03_rescwag_wugniz/assignment3.Rmd
new file mode 100644
index 0000000..07b2a80
--- /dev/null
+++ b/03_rescwag_wugniz/assignment3.Rmd
@@ -0,0 +1,74 @@
+---
+title: 'Linguistics for Cognitive Science: Assignment 3'
+author: "Felicia Saar (3818590), David-Elias Künstle (3822829)"
+date: "19.11.2015"
+output:
+  pdf_document: default
+  html_document:
+    fig_caption: yes
+---
+
+
+
+```{r, echo=FALSE, message=FALSE}
+
+library(ndl)
+
+# create sequence of learning events
+n = 1000
+dat = data.frame(
+  backgroundCue = rep("bird",  n),
+  colorCue = c(rep("red", n/2), rep("blue", n/2))
+)
+set.seed(314)
+dat = dat[sample(1:nrow(dat)),]
+rownames(dat)=1:n
+dat$category = ifelse(dat$colorCue=="red", "wug", "niz")
+
+#put in the right format
+dat$Frequency=1
+dat$Cues = paste(dat$backgroundCue, dat$colorCue, sep="_")
+dat$Outcomes = dat$category
+
+```
+```{r}
+
+#rescorla wagner function -> association between "red" and "wug"
+dat.rw = RescorlaWagner(dat, traceCue="red", traceOutcome="wug", random=F)
+plot(dat.rw)
+
+```
+```{r}
+
+#rescorla wagner function -> association between "bird" and "wug"
+dat.bw = RescorlaWagner(dat, traceCue="bird", traceOutcome="wug", random=F)
+plot(dat.bw)
+
+```
+```{r}
+
+#rescorla wagner function -> association between "bird" and "niz"
+dat.bn = RescorlaWagner(dat, traceCue="bird", traceOutcome = "niz", random = F)
+plot(dat.bn)
+
+```
+```{r}
+
+#rescorla wagner function -> association between "red" and "niz"
+dat.rn = RescorlaWagner(dat, traceCue="red", traceOutcome = "niz", random = F)
+plot(dat.rn)
+
+```
+```{r}
+
+redniz = RescorlaWagner(dat, traceCue="red", traceOutcome="niz", random=F)
+birdniz = RescorlaWagner(dat, traceCue="bird", traceOutcome="niz", random=F)
+plot(1:n, redniz$weightvector+birdniz$weightvector, type="l")
+abline(h=0)
+
+redwug = RescorlaWagner(dat, traceCue="red", traceOutcome="wug", random=F)
+birdwug = RescorlaWagner(dat, traceCue="bird", traceOutcome="wug", random=F)
+plot(1:n, redwug$weightvector+birdwug$weightvector, type="l")
+abline(h=1)
+
+```
diff --git a/03_rescwag_wugniz/rescwarl-wugniz.R b/03_rescwag_wugniz/rescwarl-wugniz.R
new file mode 100644
index 0000000..e0f9e2e
--- /dev/null
+++ b/03_rescwag_wugniz/rescwarl-wugniz.R
@@ -0,0 +1,59 @@
+
+library(ndl)
+
+# create sequence of learning events
+n = 1000
+dat = data.frame(
+  backgroundCue = rep("bird",  n),
+  colorCue = c(rep("red", n/2), rep("blue", n/2))
+)
+set.seed(314)
+dat = dat[sample(1:nrow(dat)),]
+rownames(dat)=1:n
+dat$category = ifelse(dat$colorCue=="red", "wug", "niz")
+
+#put in the right format
+dat$Frequency=1
+dat$Cues = paste(dat$backgroundCue, dat$colorCue, sep="_")
+dat$Outcomes = dat$category
+
+#rescorla wagner function -> association between "red" and "wug"
+dat.rw = RescorlaWagner(dat, traceCue="red", traceOutcome="wug", random=F)
+plot(dat.rw)
+
+#rescorla wagner function -> association between "bird" and "wug"
+dat.bw = RescorlaWagner(dat, traceCue="bird", traceOutcome="wug", random=F)
+plot(dat.bw)
+
+#rescorla wagner function -> association between "bird" and "niz"
+dat.bn = RescorlaWagner(dat, traceCue="bird", traceOutcome = "niz", random = F)
+plot(dat.bn)
+
+#rescorla wagner function -> association between "red" and "niz"
+dat.rn = RescorlaWagner(dat, traceCue="red", traceOutcome = "niz", random = F)
+plot(dat.rn)
+
+###############################
+
+redniz = RescorlaWagner(dat, traceCue="red", traceOutcome="niz", random=F)
+birdniz = RescorlaWagner(dat, traceCue="bird", traceOutcome="niz", random=F)
+plot(1:n, redniz$weightvector+birdniz$weightvector, type="l")
+abline(h=0)
+
+redwug = RescorlaWagner(dat, traceCue="red", traceOutcome="wug", random=F)
+birdwug = RescorlaWagner(dat, traceCue="bird", traceOutcome="wug", random=F)
+plot(1:n, redwug$weightvector+birdwug$weightvector, type="l")
+abline(h=1)
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/assignment3.Rmd b/assignment3.Rmd
deleted file mode 100644
index a8d1da4..0000000
--- a/assignment3.Rmd
+++ /dev/null
@@ -1,73 +0,0 @@
----
-title: 'Linguistics for Cognitive Science: Assignment 3'
-author: "Felicia Saar (3818590), David-Elias Künstle (3822829)"
-date: "19.11.2015"
-output:
-  html_document:
-    fig_caption: yes
----
-
-
-
-```{r, echo=FALSE}
-
-library(ndl)
-
-# create sequence of learning events
-n = 1000
-dat = data.frame(
-  backgroundCue = rep("bird",  n),
-  colorCue = c(rep("red", n/2), rep("blue", n/2))
-)
-set.seed(314)
-dat = dat[sample(1:nrow(dat)),]
-rownames(dat)=1:n
-dat$category = ifelse(dat$colorCue=="red", "wug", "niz")
-
-#put in the right format
-dat$Frequency=1
-dat$Cues = paste(dat$backgroundCue, dat$colorCue, sep="_")
-dat$Outcomes = dat$category
-
-```
-```{r}
-
-#rescorla wagner function -> association between "red" and "wug"
-dat.rw = RescorlaWagner(dat, traceCue="red", traceOutcome="wug", random=F)
-plot(dat.rw)
-
-```
-```{r}
-
-#rescorla wagner function -> association between "bird" and "wug"
-dat.bw = RescorlaWagner(dat, traceCue="bird", traceOutcome="wug", random=F)
-plot(dat.bw)
-
-```
-```{r}
-
-#rescorla wagner function -> association between "bird" and "niz"
-dat.bn = RescorlaWagner(dat, traceCue="bird", traceOutcome = "niz", random = F)
-plot(dat.bn)
-
-```
-```{r}
-
-#rescorla wagner function -> association between "red" and "niz"
-dat.rn = RescorlaWagner(dat, traceCue="red", traceOutcome = "niz", random = F)
-plot(dat.rn)
-
-```
-```{r}
-
-redniz = RescorlaWagner(dat, traceCue="red", traceOutcome="niz", random=F)
-birdniz = RescorlaWagner(dat, traceCue="bird", traceOutcome="niz", random=F)
-plot(1:n, redniz$weightvector+birdniz$weightvector, type="l")
-abline(h=0)
-
-redwug = RescorlaWagner(dat, traceCue="red", traceOutcome="wug", random=F)
-birdwug = RescorlaWagner(dat, traceCue="bird", traceOutcome="wug", random=F)
-plot(1:n, redwug$weightvector+birdwug$weightvector, type="l")
-abline(h=1)
-
-```