Update for T02

Tutorial_Scripts/RIntro/BIA_T01_RIntro1.Rmd

@@ -11,6 +11,8 @@ This file is part of the lecture Business Intelligence & Analytics (EESYS-BIA-M)
 ```{r Exercise: Mathematical calculations}
 2 + 3*5^2
 
+2^3^5
+
 1.4e-2
 
 1.4*exp(-2)

Tutorial_Scripts/RIntro/BIA_T02_RIntro2.Rmd

@@ -7,9 +7,11 @@ editor_options:
 
 This file is part of the lecture Business Intelligence & Analytics (EESYS-BIA-M), Information Systems and Energy Efficient Systems, University of Bamberg.
 
-
+# Part Data types
 
 ```{r Exercise: Working with lists}
+# Execute the code chunks of Tutorial 1 first to have the variables text, u, x, A, etc. loaded into your environment.
+
 # Exercise 27
 list_data <- list(text, u, x, A)
 
@@ -59,15 +61,16 @@ students[3,2]
 students$Age
 
 # Exercise 37
-students[students$Age < 30,"Name"] # colum name as identifier
+students[students$Age < 30,"Name"] # column name as identifier
 students[students$Age < 30,2] # column index as identifier
 students[students$Age < 30,]$Name # get a data.frame and then select the variable by $ operator
 ```
 
-  
+# Your first project: The shower data set
+
 
 ```{r Load and inspect data}
-# Task 1 clone git repository
+# Task 1 clone / pull the git repository
 
 # Task 2
 # Read data. Remember the relative path
@@ -151,3 +154,18 @@ write.csv2(x = Shower[Shower$Hh_ID != 8899,], file="../../output/cleaned_shower_
 
 After cleaning data we have stored the data to the folder "output".
 
+
+# Cooldown exercise
+```{r Cooldown exercise}
+Shower <- read.csv2("../../data/Shower_data.csv")
+summary(Shower)
+Shower$group <- as.factor(Shower$group)
+
+Shower_one_to_ten <- Shower[Shower$Shower %in% 1:10, ]
+tapply(Shower_one_to_ten$Volume, Shower_one_to_ten$group, mean, na.rm=T)
+
+Shower_more_than_ten <- Shower[!Shower$Shower %in% 1:10, ]
+tapply(Shower_more_than_ten$Volume, Shower_more_than_ten$group, mean, na.rm=T)
+```
+
+

Tutorial_Scripts/RIntro/BIA_T02_RIntro2_exercise.Rmd

@@ -9,6 +9,8 @@ This file is part of the lecture Business Intelligence & Analytics (EESYS-BIA-M)
 
 
 ```{r Exercise: Working with lists}
+# Execute the code chunks of Tutorial 1 first to have the variables text, u, x, A, etc. loaded into your environment.
+
 # Exercise 27
 
 
@@ -114,3 +116,8 @@ Nationality <- as.factor(c("DE","US","DE","SE"))
 
 After cleaning data we have stored the data to the folder "output".
 
+
+```{r Cooldown exercise}
+
+```
+

Tutorial_Scripts/RIntro/BIA_T03_RIntro3.Rmd

@@ -6,17 +6,6 @@ editor_options:
 ---
 
 This file is part of the lecture Business Intelligence & Analytics (EESYS-BIA-M), Information Systems and Energy Efficient Systems, University of Bamberg.
-```{r Solution for Cooldown exercise}
-Shower <- read.csv2("../../data/Shower_data.csv")
-summary(Shower)
-Shower$group <- as.factor(Shower$group)
-
-Shower_one_to_ten <- Shower[Shower$Shower %in% 1:10, ]
-tapply(Shower_one_to_ten$Volume, Shower_one_to_ten$group, mean, na.rm=T)
-
-Shower_more_than_ten <- Shower[!Shower$Shower %in% 1:10, ]
-tapply(Shower_more_than_ten$Volume, Shower_more_than_ten$group, mean, na.rm=T)
-```
 
 
 ```{r Functions}