diff --git a/tutorial_page.Rmd b/tutorial_page.Rmd
index 6c91137de24d79380c48b22a75d08dd7d47989be..ced54b142b2f83d322d01cb3501cc87bf8bfa1e7 100644
--- a/tutorial_page.Rmd
+++ b/tutorial_page.Rmd
@@ -25,7 +25,7 @@ Link zum Datensatz auf Kaggle: https://www.kaggle.com/code/karnikakapoor/board-g
### Inhalt
-Der Datensatz umfasst 20.343 Einträge und enthält verschiedene Informationen zu Brettspielen. Hier sind die Spalten und ihre jeweiligen Inhalte:
+Der Datensatz umfasst 20.343 Einträge und enthält verschiedene Informationen zu Brettspielen. Aus Darstellungsgründen wurde der Datensatz allerdings auf 500 Einträge reduziert. Hier sind die Spalten und ihre jeweiligen Inhalte:
**ID**: Eine eindeutige Identifikationsnummer für jedes Brettspiel im Datensatz.*(Integer)*\
**Name:** Der Name des Brettspiels.*(String)*\
@@ -217,9 +217,9 @@ quiz(
## Datenanalyse
In diesem Teil wird beschrieben, wie man verschiedene Daten mit Funktionen ermitteln kann.\
-Hierfuer sollte man sich die Daten erneut anschauen.\
-Fuer diesen Teil ist es wichtig zu wissen, wie man auf eine Spalte zugreifen kann. Dies macht man in dem man die Variable in dem der Datensatz gespeichert ist (hier gameData) angibt und den Spaltennamen in entweder zwei eckigen Klammern oder hinter einem $ Zeichen definiert.\
-Die Syntax waere dann beispielsweise:\
+Hierfür sollte man sich die Daten erneut anschauen.\
+Für diesen Teil ist es wichtig zu wissen, wie man auf eine Spalte zugreifen kann. Dies macht man in dem man die Variable in dem der Datensatz gespeichert ist (hier gameData) angibt und den Spaltennamen in entweder zwei eckigen Klammern oder hinter einem $ Zeichen definiert.\
+Die Syntax wäre dann beispielsweise:\
```data[["column"]])``` oder ```data$column```, bzw. ```data$"spaced column name"```\
\
Die Tabelle unten zeigt alle Daten aus dem Datensatz. Mit den Pfeilen in der oberen Reihe kann man die durch die Spalten schalten.
@@ -230,10 +230,10 @@ head(gameData)
### Mittelwert
-Der Mittelwert bestimmt den Durchschnitt aller gegebenen Werte. Die Rechnung dafuer ist:\
+Der Mittelwert bestimmt den Durchschnitt aller gegebenen Werte. Die Rechnung dafür ist:\
$(x_{1} + x_{2} + \cdots + x_{n}) / x$\
\
-Um den Mittelwert einer Spalte zu bestimmen, vewendet man die 'mean()' Funktion verwenden. In diese setzt man die Variable in der die Daten gespeichert sind (gameData) und gibt die gewuenschte Spalte an.\
+Um den Mittelwert einer Spalte zu bestimmen, vewendet man die 'mean()' Funktion verwenden. In diese setzt man die Variable in der die Daten gespeichert sind (gameData) und gibt die gewünschte Spalte an.\
\
Bestimmen Sie den Mittelwert von "Play Time".
```{r mean, exercise=TRUE}
@@ -284,18 +284,18 @@ Sie sollten hier den Wert 77.91056 bekommen.
### Lineare Regression
-Die Lineare Regression bestimmt das Verhaeltnis zwischen zwei Werten(-sets).\
+Die Lineare Regression bestimmt das Verhältnis zwischen zwei Werten(-sets).\
\
-Die Varianz wird durch die 'lm()' Funktion bestimmt Hier uebergibt man Daten welche mit einem Tilde-Symbol (~) verbunden sind, also beispielsweise ```lm(x~y)```.\
-Bestimmen sie die Lineare Regression mit "Users Rated" im Verhaeltnis zu "Owned Users".
+Die Varianz wird durch die 'lm()' Funktion bestimmt Hier übergibt man Daten welche mit einem Tilde-Symbol (~) verbunden sind, also beispielsweise ```lm(x~y)```.\
+Bestimmen sie die Lineare Regression mit "Users Rated" im Verhältnis zu "Owned Users".
```{r linear-regression, exercise=TRUE}
raters <- gameData$"Users Rated"
owned <- gameData$"Owned Users"
```
-Falls man etwas mehr information will, kann man die Eingabe (oder die Variale in welche man dies gespeichert hat) noch in die ```summary()``` Funktion schreiben.\
+Falls man etwas mehr Information will, kann man die Eingabe (oder die Variale in welche man dies gespeichert hat) noch in die ```summary()``` Funktion schreiben.\
Weiterhin kann man dies auf ein Plot abbilden. Dazu verwendet man die ```plot()``` Funktion in welche man einen x und y Wert eingibt, zusammen mit Optionen wie das Plot aussehen soll. Mehr information dazu findet man [in der Dokumentation](https://www.rdocumentation.org/packages/graphics/versions/3.6.2/topics/plot).\
-Mit ```abline()``` kann man die Regressionslinie der lm Funktion abbilden. Dazu wird die lm Funktion, oder die Variable in der diese gespeichert ist, an ```abline()``` uebergeben.\
+Mit ```abline()``` kann man die Regressionslinie der lm Funktion abbilden. Dazu wird die lm Funktion, oder die Variable in der diese gespeichert ist, an ```abline()``` übergeben.\
```{r lm-plot-example}
raters <- gameData$"Users Rated"
owned <- gameData$"Owned Users"
@@ -318,7 +318,7 @@ plot(, , pch = 16, col = "blue")
### Hypothesentest
-R hat Funktionen zum Testen von Hypothesen. Hier kann man nun den [T-Test](https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/t.test) anwenden. In der Funktion ```t.test()``` werden die beiden Wertesets eingegeben. Der ausgegebene p-Wert (p-value) kann dann mit dem Signifikanzwert (typischerweise 5%(0.05)) verglichen werden. Ist der Wert groesser als 0.05 kann man annehmen, dass die Hypothese stimmt. Einen Testdurchschnitt kann man mit dem Parameter ```mu={value}``` angeben.
+R hat Funktionen zum Testen von Hypothesen. Hier kann man nun den [T-Test](https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/t.test) anwenden. In der Funktion ```t.test()``` werden die beiden Wertesets eingegeben. Der ausgegebene p-Wert (p-value) kann dann mit dem Signifikanzwert (typischerweise 5%(0.05)) verglichen werden. Ist der Wert grösser als 0.05 kann man annehmen, dass die Hypothese stimmt. Einen Testdurchschnitt kann man mit dem Parameter ```mu={value}``` angeben.
```{r hypothesis-test, exercise=TRUE, exercise.lines=4}
ptime <- gameData$"Play Time"
@@ -457,11 +457,11 @@ Lino ist verantwortlich für die Ausarbeitung des Datenanalyse-Abschnitts.
### Maximilian Fronmüller
-Maxi hat sich auf die Erstellung des Ergebnispräsentation-Abschnitts konzentriert.
+Maximilian hat sich auf die Erstellung des Ergebnispräsentation-Abschnitts konzentriert.
### Nikolay Nikolaev
-Nikolay hat an die Abschnitte Datenbasis und Datenaufbereitung gearbeitet.
+Nikolay hat an den Abschnitten Datenbasis und Datenaufbereitung gearbeitet.
diff --git a/tutorial_page.html b/tutorial_page.html
index 4161d7860ad1745207964ac548b1d3ca123bbb3b..29b209ab8824dd996fb9425f872bb2ef6eb57e6d 100644
--- a/tutorial_page.html
+++ b/tutorial_page.html
@@ -416,7 +416,7 @@ Die Tabelle unten zeigt alle Daten aus dem Datensatz. Mit den Pfeilen in
der oberen Reihe kann man die durch die Spalten schalten.
<div data-pagedtable="false">
<script data-pagedtable-source type="application/json">
-{"columns":[{"label":["ID"],"name":[1],"type":["dbl"],"align":["right"]},{"label":["Name"],"name":[2],"type":["chr"],"align":["left"]},{"label":["Year Published"],"name":[3],"type":["dbl"],"align":["right"]},{"label":["Min Players"],"name":[4],"type":["dbl"],"align":["right"]},{"label":["Max Players"],"name":[5],"type":["dbl"],"align":["right"]},{"label":["Play Time"],"name":[6],"type":["dbl"],"align":["right"]},{"label":["Min Age"],"name":[7],"type":["dbl"],"align":["right"]},{"label":["Users Rated"],"name":[8],"type":["dbl"],"align":["right"]},{"label":["Rating Average"],"name":[9],"type":["dbl"],"align":["right"]},{"label":["BGG Rank"],"name":[10],"type":["dbl"],"align":["right"]},{"label":["Complexity Average"],"name":[11],"type":["dbl"],"align":["right"]},{"label":["Owned Users"],"name":[12],"type":["dbl"],"align":["right"]},{"label":["Mechanics"],"name":[13],"type":["chr"],"align":["left"]},{"label":["Domains"],"name":[14],"type":["chr"],"align":["left"]}],"data":[{"1":"174430","2":"Gloomhaven","3":"2017","4":"1","5":"4","6":"120","7":"14","8":"42055","9":"8.79","10":"1","11":"3.86","12":"68323","13":"Action Queue, Action Retrieval, Campaign / Battle Card Driven, Card Play Conflict Resolution, Communication Limits, Cooperative Game, Deck Construction, Deck Bag and Pool Building, Grid Movement, Hand Management, Hexagon Grid, Legacy Game, Modular Board, Once-Per-Game Abilities, Scenario / Mission / Campaign Game, Simultaneous Action Selection, Solo / Solitaire Game, Storytelling, Variable Player Powers","14":"Strategy Games, Thematic Games"},{"1":"161936","2":"Pandemic Legacy: Season 1","3":"2015","4":"2","5":"4","6":"60","7":"13","8":"41643","9":"8.61","10":"2","11":"2.84","12":"65294","13":"Action Points, Cooperative Game, Hand Management, Legacy Game, Point to Point Movement, Set Collection, Trading, Variable Player Powers","14":"Strategy Games, Thematic Games"},{"1":"224517","2":"Brass: Birmingham","3":"2018","4":"2","5":"4","6":"120","7":"14","8":"19217","9":"8.66","10":"3","11":"3.91","12":"28785","13":"Hand Management, Income, Loans, Market, Network and Route Building, Score-and-Reset Game, Tech Trees / Tech Tracks, Turn Order: Stat-Based, Variable Set-up","14":"Strategy Games"},{"1":"167791","2":"Terraforming Mars","3":"2016","4":"1","5":"5","6":"120","7":"12","8":"64864","9":"8.43","10":"4","11":"3.24","12":"87099","13":"Card Drafting, Drafting, End Game Bonuses, Hand Management, Hexagon Grid, Income, Set Collection, Solo / Solitaire Game, Take That, Tile Placement, Turn Order: Progressive, Variable Player Powers","14":"Strategy Games"},{"1":"233078","2":"Twilight Imperium: Fourth Edition","3":"2017","4":"3","5":"6","6":"480","7":"14","8":"13468","9":"8.70","10":"5","11":"4.22","12":"16831","13":"Action Drafting, Area Majority / Influence, Area-Impulse, Dice Rolling, Follow, Grid Movement, Hexagon Grid, Modular Board, Trading, Variable Phase Order, Variable Player Powers, Voting","14":"Strategy Games, Thematic Games"},{"1":"291457","2":"Gloomhaven: Jaws of the Lion","3":"2020","4":"1","5":"4","6":"120","7":"14","8":"8392","9":"8.87","10":"6","11":"3.55","12":"21609","13":"Action Queue, Campaign / Battle Card Driven, Communication Limits, Cooperative Game, Critical Hits and Failures, Deck Construction, Grid Movement, Hand Management, Hexagon Grid, Legacy Game, Line of Sight, Once-Per-Game Abilities, Scenario / Mission / Campaign Game, Simultaneous Action Selection, Solo / Solitaire Game, Variable Player Powers","14":"Strategy Games, Thematic Games"}],"options":{"columns":{"min":{},"max":[10]},"rows":{"min":[10],"max":[10]},"pages":{}}}
+{"columns":[{"label":["ID"],"name":[1],"type":["dbl"],"align":["right"]},{"label":["Name"],"name":[2],"type":["chr"],"align":["left"]},{"label":["Year Published"],"name":[3],"type":["dbl"],"align":["right"]},{"label":["Min Players"],"name":[4],"type":["dbl"],"align":["right"]},{"label":["Max Players"],"name":[5],"type":["dbl"],"align":["right"]},{"label":["Play Time"],"name":[6],"type":["dbl"],"align":["right"]},{"label":["Min Age"],"name":[7],"type":["dbl"],"align":["right"]},{"label":["Users Rated"],"name":[8],"type":["dbl"],"align":["right"]},{"label":["Rating Average"],"name":[9],"type":["dbl"],"align":["right"]},{"label":["BGG Rank"],"name":[10],"type":["dbl"],"align":["right"]},{"label":["Complexity Average"],"name":[11],"type":["dbl"],"align":["right"]},{"label":["Owned Users"],"name":[12],"type":["dbl"],"align":["right"]},{"label":["Mechanics"],"name":[13],"type":["chr"],"align":["left"]},{"label":["Domains"],"name":[14],"type":["chr"],"align":["left"]}],"data":[{"1":"174430","2":"Gloomhaven","3":"2017","4":"1","5":"4","6":"120","7":"14","8":"42055","9":"879","10":"1","11":"386","12":"68323","13":"Action Queue, Action Retrieval, Campaign / Battle Card Driven, Card Play Conflict Resolution, Communication Limits, Cooperative Game, Deck Construction, Deck Bag and Pool Building, Grid Movement, Hand Management, Hexagon Grid, Legacy Game, Modular Board, Once-Per-Game Abilities, Scenario / Mission / Campaign Game, Simultaneous Action Selection, Solo / Solitaire Game, Storytelling, Variable Player Powers","14":"Strategy Games, Thematic Games"},{"1":"161936","2":"Pandemic Legacy: Season 1","3":"2015","4":"2","5":"4","6":"60","7":"13","8":"41643","9":"861","10":"2","11":"284","12":"65294","13":"Action Points, Cooperative Game, Hand Management, Legacy Game, Point to Point Movement, Set Collection, Trading, Variable Player Powers","14":"Strategy Games, Thematic Games"},{"1":"224517","2":"Brass: Birmingham","3":"2018","4":"2","5":"4","6":"120","7":"14","8":"19217","9":"866","10":"3","11":"391","12":"28785","13":"Hand Management, Income, Loans, Market, Network and Route Building, Score-and-Reset Game, Tech Trees / Tech Tracks, Turn Order: Stat-Based, Variable Set-up","14":"Strategy Games"},{"1":"167791","2":"Terraforming Mars","3":"2016","4":"1","5":"5","6":"120","7":"12","8":"64864","9":"843","10":"4","11":"324","12":"87099","13":"Card Drafting, Drafting, End Game Bonuses, Hand Management, Hexagon Grid, Income, Set Collection, Solo / Solitaire Game, Take That, Tile Placement, Turn Order: Progressive, Variable Player Powers","14":"Strategy Games"},{"1":"233078","2":"Twilight Imperium: Fourth Edition","3":"2017","4":"3","5":"6","6":"480","7":"14","8":"13468","9":"870","10":"5","11":"422","12":"16831","13":"Action Drafting, Area Majority / Influence, Area-Impulse, Dice Rolling, Follow, Grid Movement, Hexagon Grid, Modular Board, Trading, Variable Phase Order, Variable Player Powers, Voting","14":"Strategy Games, Thematic Games"},{"1":"291457","2":"Gloomhaven: Jaws of the Lion","3":"2020","4":"1","5":"4","6":"120","7":"14","8":"8392","9":"887","10":"6","11":"355","12":"21609","13":"Action Queue, Campaign / Battle Card Driven, Communication Limits, Cooperative Game, Critical Hits and Failures, Deck Construction, Grid Movement, Hand Management, Hexagon Grid, Legacy Game, Line of Sight, Once-Per-Game Abilities, Scenario / Mission / Campaign Game, Simultaneous Action Selection, Solo / Solitaire Game, Variable Player Powers","14":"Strategy Games, Thematic Games"}],"options":{"columns":{"min":{},"max":[10]},"rows":{"min":[10],"max":[10]},"pages":{}}}
</script>
</div>
<p><br />
@@ -617,8 +617,9 @@ Streuparameter abbildet und damit einen ersten groben Überblick über
eine Verteilung gibt. Meistens verwendet man einen Boxplot um schnell
eine Übersicht über Median, Quartile, Minimal- und Maximalwerte sowie
Ausreißer zu erhalten.<br />
-Folgend ein Beispiel:
-<img src="tutorial_page_files/figure-html/ggplot-1.png" width="624" /><br />
+Folgend ein Beispiel:</p>
+<pre><code>## Warning: Removed 1 rows containing missing values (`stat_boxplot()`).</code></pre>
+<p><img src="tutorial_page_files/figure-html/ggplot-1.png" width="624" /><br />
<br />
Anhand des Beispiels nun ein kleines Quiz zur Verdeutlichung der
Begrifflichkeiten:<br />
@@ -713,7 +714,7 @@ konzentriert.</p>
</div>
<div id="section-nikolay-nikolaev" class="section level3">
<h3>Nikolay Nikolaev</h3>
-<p>Nikolay hat an die Abschnitte Datenbasis und Datenaufbereitung
+<p>Nikolay hat an den Abschnitten Datenbasis und Datenaufbereitung
gearbeitet.</p>
<p>
<script type="application/shiny-prerendered" data-context="server-start">
@@ -721,7 +722,7 @@ library(learnr)
library(readxl)
library("ggplot2")
options(scipen = 10)
-gameData <- read_excel("bgg_dataset.xlsx", sheet = "Sheet")
+gameData <- read_excel("bgg_dataset.xlsx", sheet = "Sheet2")
knitr::opts_chunk$set(echo = FALSE)
</script>
@@ -756,7 +757,7 @@ output$`tutorial-exercise-install-readxl-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "install-readxl", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "install-readxl",
code = "install.packages(\"readxl\")\nlibrary (readxl)",
@@ -797,7 +798,7 @@ output$`tutorial-exercise-read-data-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "read-data", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "read-data",
code = "gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
@@ -838,7 +839,7 @@ output$`tutorial-exercise-show-data-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "show-data", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "show-data",
code = "gameData", opts = list(label = "\"show-data\"", exercise = "TRUE"),
@@ -878,7 +879,7 @@ output$`tutorial-exercise-read-column-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "read-column", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "read-column",
code = "gameData$`Year Published`", opts = list(label = "\"read-column\"",
@@ -919,7 +920,7 @@ output$`tutorial-exercise-read-mechanics-column-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "read-mechanics-column", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "read-mechanics-column",
code = "", opts = list(label = "\"read-mechanics-column\"",
@@ -959,7 +960,7 @@ output$`tutorial-exercise-remove-empties-column-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "remove-empties-column", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "remove-empties-column",
code = "gameData$`Year Published` <- trimws(gameData$`Year Published`)\ngameData$`Year Published`",
@@ -1001,7 +1002,7 @@ output$`tutorial-exercise-remove-empties-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "remove-empties", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "remove-empties",
code = "gameData <- lapply(gameData, trimws)\ngameData",
@@ -1042,7 +1043,7 @@ output$`tutorial-exercise-to-lowercase-column-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "to-lowercase-column", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "to-lowercase-column",
code = "gameData$`Mechanics` <- tolower(gameData$`Mechanics`)\ngameData$`Mechanics`",
@@ -1084,7 +1085,7 @@ output$`tutorial-exercise-replace-variable-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "replace-variable", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "replace-variable",
code = "gameData$`Mechanics` <- gsub(\"Action\", \"!!!ACTION!!!\", gameData$`Mechanics`)\ngameData$`Mechanics`",
@@ -1126,7 +1127,7 @@ output$`tutorial-exercise-replace-missing-variable-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "replace-missing-variable", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "replace-missing-variable",
code = "gameData$`Rating Average`[is.na(gameData$`Rating Average`)] <- mean(gameData$`Rating Average`, na.rm = TRUE)",
@@ -1167,7 +1168,7 @@ output$`tutorial-exercise-remove-duplicates-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "remove-duplicates", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "remove-duplicates",
code = "vector <- c(1, 2, 3, 3, 5, 2, 1, 7, 10, 5)\nvector <- unique(vector)\n\nvector",
@@ -1209,7 +1210,7 @@ output$`tutorial-exercise-replace-special-chars-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "replace-special-chars", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "replace-special-chars",
code = "gameData$`Mechanics` <- gsub(\"[^a-zA-Z0-9 ]\", \"\", gameData$`Mechanics`)\ngameData$`Mechanics`",
@@ -1243,19 +1244,19 @@ learnr:::store_exercise_cache(structure(list(label = "replace-special-chars", gl
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "second-quiz-1",
question = structure("Mit welchem R-Befehl lassen sich Packages installieren?", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_be1d985",
+ "character")), answers = list(structure(list(id = "lnr_ans_28e6919",
option = "install.packages()", value = "install.packages()",
label = structure("install.packages()", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_e89a2ef",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_8939d84",
option = "add.packages()", value = "add.packages()",
label = structure("add.packages()", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_e696377",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_358ced2",
option = "install.library()", value = "install.library()",
label = structure("install.library()", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_bdf59b7",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_45f895c",
option = "install()", value = "install()", label = structure("install()", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
"tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html",
@@ -1266,7 +1267,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
"character")), message = NULL, post_message = NULL), ids = list(
answer = "second-quiz-1-answer", question = "second-quiz-1"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 601899230.719719, options = list()), class = c("learnr_radio",
+ seed = 1026236034.02212, options = list()), class = c("learnr_radio",
"tutorial_question")), session = session)
</script>
@@ -1274,16 +1275,16 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "second-quiz-2",
question = structure("Mit welchem R-Befehl lassen sich die installierten Packages initialisieren?", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_e84571d",
+ "character")), answers = list(structure(list(id = "lnr_ans_f1b5679",
option = "use()", value = "use()", label = structure("use()", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_2781b16",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_8f59b04",
option = "library()", value = "library()", label = structure("library()", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_84efd9b",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_919415a",
option = "init()", value = "init()", label = structure("init()", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_e2e3021",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_619169",
option = "install.packages()", value = "install.packages()",
label = structure("install.packages()", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
@@ -1295,23 +1296,23 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
"character")), message = NULL, post_message = NULL), ids = list(
answer = "second-quiz-2-answer", question = "second-quiz-2"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 460423745.285598, options = list()), class = c("learnr_radio",
+ seed = 1836941299.14461, options = list()), class = c("learnr_radio",
"tutorial_question")), session = session)
</script>
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "second-quiz-3",
question = structure("Welcher Packet benutzen wir, um XLSX-Dateien zu lesen?", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_10e2d44",
+ "character")), answers = list(structure(list(id = "lnr_ans_23d35dc",
option = "readxl()", value = "readxl()", label = structure("readxl()", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_630dc3d",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_6f5b913",
option = "readxls()", value = "readxls()", label = structure("readxls()", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_30358b7",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_8c40473",
option = "readexcel()", value = "readexcel()", label = structure("readexcel()", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_3a0342f",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_9e22175",
option = "excelread()", value = "excelread()", label = structure("excelread()", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
"tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html",
@@ -1322,7 +1323,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
"character")), message = NULL, post_message = NULL), ids = list(
answer = "second-quiz-3-answer", question = "second-quiz-3"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 1284267179.90197, options = list()), class = c("learnr_radio",
+ seed = 1060942811.50596, options = list()), class = c("learnr_radio",
"tutorial_question")), session = session)
</script>
@@ -1330,19 +1331,19 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "second-quiz-4",
question = structure("Wie lassen sich einzelne Spalten aus dem Datensatz auslesen?", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_f675a70",
+ "character")), answers = list(structure(list(id = "lnr_ans_7179e0e",
option = "dataset&\\`column\\`", value = "dataset&\\`column\\`",
label = structure("dataset&`column`", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_d93701d",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_ebf5e08",
option = "column$dataset", value = "column$dataset",
label = structure("column$dataset", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_e0dd963",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_5ca91cf",
option = "dataset%\\`column\\`", value = "dataset%\\`column\\`",
label = structure("dataset%`column`", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_267e7db",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_2aa2cc5",
option = "dataset$\\`column\\`", value = "dataset$\\`column\\`",
label = structure("dataset$`column`", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
@@ -1354,7 +1355,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
"character")), message = NULL, post_message = NULL), ids = list(
answer = "second-quiz-4-answer", question = "second-quiz-4"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 678218021.18418, options = list()), class = c("learnr_radio",
+ seed = 81482597.4620567, options = list()), class = c("learnr_radio",
"tutorial_question")), session = session)
</script>
@@ -1369,7 +1370,7 @@ output$`tutorial-exercise-mean-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "mean", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "mean",
code = "\n\n", opts = list(label = "\"mean\"", exercise = "TRUE"),
@@ -1408,7 +1409,7 @@ output$`tutorial-exercise-median-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "median", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "median",
code = "ptime <- gameData[[\"Play Time\"]]", opts = list(
@@ -1449,7 +1450,7 @@ output$`tutorial-exercise-variance-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "variance", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "variance",
code = "ptime <- gameData$\"Play Time\"", opts = list(label = "\"variance\"",
@@ -1490,7 +1491,7 @@ output$`tutorial-exercise-standard-deviation-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "standard-deviation", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "standard-deviation",
code = "ptime <- gameData$\"Play Time\"", opts = list(label = "\"standard-deviation\"",
@@ -1531,7 +1532,7 @@ output$`tutorial-exercise-linear-regression-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "linear-regression", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "linear-regression",
code = "raters <- gameData$\"Users Rated\"\nowned <- gameData$\"Owned Users\"",
@@ -1572,7 +1573,7 @@ output$`tutorial-exercise-lm-plot-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "lm-plot", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "lm-plot",
code = "raters <- gameData$\"Users Rated\"\nowned <- gameData$\"Owned Users\"\ncavg <- gameData$\"Complexity Average\"\nx = lm()\nplot(, , pch = 16, col = \"blue\")\n",
@@ -1615,7 +1616,7 @@ output$`tutorial-exercise-hypothesis-test-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "hypothesis-test", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "hypothesis-test",
code = "ptime <- gameData$\"Play Time\"\nrated <- gameData$\"Users Rated\"",
@@ -1650,10 +1651,10 @@ learnr:::store_exercise_cache(structure(list(label = "hypothesis-test", global_s
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "hypothesis-quiz-1",
question = structure("Die durchschnittliche Spielzeit betraegt 30 minuten.", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_9bb17a5",
+ "character")), answers = list(structure(list(id = "lnr_ans_68dc7e2",
option = "Wahr", value = "Wahr", label = structure("Wahr", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_1f3a562",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_2495450",
option = "Falsch", value = "Falsch", label = structure("Falsch", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
"tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html",
@@ -1664,7 +1665,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
"character")), message = NULL, post_message = NULL), ids = list(
answer = "hypothesis-quiz-1-answer", question = "hypothesis-quiz-1"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 1544183715.28093, options = list()), class = c("learnr_radio",
+ seed = 1460040477.32012, options = list()), class = c("learnr_radio",
"tutorial_question")), session = session)
</script>
@@ -1672,10 +1673,10 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "hypothesis-quiz-2",
question = structure("Pro Spiel haben 15000 leute eine Bewertung gegeben.", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_495a2cf",
+ "character")), answers = list(structure(list(id = "lnr_ans_37361e0",
option = "Wahr", value = "Wahr", label = structure("Wahr", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_731cf7b",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_2dec6a",
option = "Falsch", value = "Falsch", label = structure("Falsch", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
"tutorial_quiz_answer"))), button_labels = list(submit = structure("<span data-i18n=\"button.questionsubmit\">Submit Answer<\u002fspan>", html = TRUE, class = c("html",
@@ -1686,7 +1687,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
"character")), message = NULL, post_message = NULL), ids = list(
answer = "hypothesis-quiz-2-answer", question = "hypothesis-quiz-2"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 2019060634.0598, options = list()), class = c("learnr_radio",
+ seed = 41464897.4806914, options = list()), class = c("learnr_radio",
"tutorial_question")), session = session)
</script>
@@ -1701,7 +1702,7 @@ output$`tutorial-exercise-plotExercise-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "plotExercise", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "plotExercise",
code = "", opts = list(label = "\"plotExercise\"", exercise = "TRUE"),
@@ -1732,20 +1733,20 @@ learnr:::store_exercise_cache(structure(list(label = "plotExercise", global_setu
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "quiz-ggplot-1",
question = structure("Was ist der Median im Diagramm?", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_7e8eeec",
+ "character")), answers = list(structure(list(id = "lnr_ans_be1d353",
option = "ein vertikaler Strich", value = "ein vertikaler Strich",
label = structure("ein vertikaler Strich", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_1cc8cbd",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_57b8735",
option = "die Höhe der Box", value = "die Höhe der Box",
label = structure("die Höhe der Box", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_a0d5cc6",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_7f694c3",
option = "ein horizontaler Strich in der Mitter der Box",
value = "ein horizontaler Strich in der Mitter der Box",
label = structure("ein horizontaler Strich in der Mitter der Box", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_e368d73",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_5a92d82",
option = "das untere Ende der Box", value = "das untere Ende der Box",
label = structure("das untere Ende der Box", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
@@ -1757,7 +1758,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
"character")), message = NULL, post_message = NULL), ids = list(
answer = "quiz-ggplot-1-answer", question = "quiz-ggplot-1"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 1433709425.83238, options = list()), class = c("learnr_radio",
+ seed = 401580934.812999, options = list()), class = c("learnr_radio",
"tutorial_question")), session = session)
</script>
@@ -1765,19 +1766,19 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_checkbox", label = "quiz-ggplot-2",
question = structure("Was sind die Quartile im Diagramm?(Es sind mehrere Antworten möglich)", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_2854118",
+ "character")), answers = list(structure(list(id = "lnr_ans_9b347fe",
option = "das obere Ende der Box", value = "das obere Ende der Box",
label = structure("das obere Ende der Box", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_c6611ef",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_d068302",
option = "Punkte oberhalb der Box", value = "Punkte oberhalb der Box",
label = structure("Punkte oberhalb der Box", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_8e1fc07",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_19824d6",
option = "ein Drittel des vertikalen Strichs", value = "ein Drittel des vertikalen Strichs",
label = structure("ein Drittel des vertikalen Strichs", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_3dedaa3",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_aa5fddd",
option = "das untere Ende der Box", value = "das untere Ende der Box",
label = structure("das untere Ende der Box", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
@@ -1789,26 +1790,26 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_checkbox", lab
"character")), message = NULL, post_message = NULL), ids = list(
answer = "quiz-ggplot-2-answer", question = "quiz-ggplot-2"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 211417526.901551, options = list()), class = c("learnr_checkbox",
+ seed = 1203678523.43949, options = list()), class = c("learnr_checkbox",
"tutorial_question")), session = session)
</script>
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "quiz-ggplot-3",
question = structure("Was sind die Maximalwerte im Diagramm?", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_ebe3230",
+ "character")), answers = list(structure(list(id = "lnr_ans_9a636fa",
option = "Punkte oberhalb der Box", value = "Punkte oberhalb der Box",
label = structure("Punkte oberhalb der Box", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_a62487",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_49a246b",
option = "die Spitzen des vertikalen Strichs", value = "die Spitzen des vertikalen Strichs",
label = structure("die Spitzen des vertikalen Strichs", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_c378148",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_4e8d307",
option = "die x-Achse und die y-Achse", value = "die x-Achse und die y-Achse",
label = structure("die x-Achse und die y-Achse", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_3d8920e",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_e518635",
option = "die Flaeche der Box", value = "die Flaeche der Box",
label = structure("die Flaeche der Box", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
@@ -1820,7 +1821,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
"character")), message = NULL, post_message = NULL), ids = list(
answer = "quiz-ggplot-3-answer", question = "quiz-ggplot-3"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 1430753873.33375, options = list()), class = c("learnr_radio",
+ seed = 1131623528.97305, options = list()), class = c("learnr_radio",
"tutorial_question")), session = session)
</script>
@@ -1828,15 +1829,15 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
<script type="application/shiny-prerendered" data-context="server">
learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label = "quiz-ggplot-4",
question = structure("An was erkennt man im Diagramm die Ausreißer?", html = TRUE, class = c("html",
- "character")), answers = list(structure(list(id = "lnr_ans_40465c9",
+ "character")), answers = list(structure(list(id = "lnr_ans_9997b2c",
option = "es sind Punkte außerhalb der Box", value = "es sind Punkte außerhalb der Box",
label = structure("es sind Punkte außerhalb der Box", html = TRUE, class = c("html",
"character")), correct = TRUE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_678c963",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_d33807d",
option = "an der Größe der Box", value = "an der Größe der Box",
label = structure("an der Größe der Box", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
- "tutorial_quiz_answer")), structure(list(id = "lnr_ans_3c1c65d",
+ "tutorial_quiz_answer")), structure(list(id = "lnr_ans_4adcfdd",
option = "durch schlechtes Verhalten", value = "durch schlechtes Verhalten",
label = structure("durch schlechtes Verhalten", html = TRUE, class = c("html",
"character")), correct = FALSE, message = NULL, type = "literal"), class = c("tutorial_question_answer",
@@ -1848,7 +1849,7 @@ learnr:::question_prerendered_chunk(structure(list(type = "learnr_radio", label
"character")), message = NULL, post_message = NULL), ids = list(
answer = "quiz-ggplot-4-answer", question = "quiz-ggplot-4"),
loading = NULL, random_answer_order = FALSE, allow_retry = FALSE,
- seed = 319161909.851379, options = list()), class = c("learnr_radio",
+ seed = 1326054475.88251, options = list()), class = c("learnr_radio",
"tutorial_question")), session = session)
</script>
@@ -1863,7 +1864,7 @@ output$`tutorial-exercise-barplotExercise-output` <- renderUI({
<script type="application/shiny-prerendered" data-context="server">
learnr:::store_exercise_cache(structure(list(label = "barplotExercise", global_setup = structure(c("library(learnr)",
"library(readxl)", "library(\"ggplot2\")", "options(scipen = 10)",
-"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet\")",
+"gameData <- read_excel(\"bgg_dataset.xlsx\", sheet = \"Sheet2\")",
"knitr::opts_chunk$set(echo = FALSE)"), chunk_opts = list(label = "setup",
include = FALSE)), setup = NULL, chunks = list(list(label = "barplotExercise",
code = "\n", opts = list(label = "\"barplotExercise\"", exercise = "TRUE"),
@@ -1899,7 +1900,7 @@ learnr:::store_exercise_cache(structure(list(label = "barplotExercise", global_s
<!--/html_preserve-->
<!--html_preserve-->
<script type="application/shiny-prerendered" data-context="execution_dependencies">
-{"type":"list","attributes":{"names":{"type":"character","attributes":{},"value":["packages"]}},"value":[{"type":"list","attributes":{"names":{"type":"character","attributes":{},"value":["packages","version"]},"class":{"type":"character","attributes":{},"value":["data.frame"]},"row.names":{"type":"integer","attributes":{},"value":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65]}},"value":[{"type":"character","attributes":{},"value":["backports","base","bslib","cachem","cellranger","checkmate","cli","colorspace","commonmark","compiler","datasets","digest","dplyr","ellipsis","evaluate","fansi","farver","fastmap","fontawesome","generics","ggplot2","glue","graphics","grDevices","grid","gtable","highr","htmltools","htmlwidgets","httpuv","jquerylib","jsonlite","knitr","labeling","later","learnr","lifecycle","magrittr","markdown","methods","mime","munsell","pillar","pkgconfig","promises","R6","Rcpp","readxl","rlang","rmarkdown","rprojroot","sass","scales","shiny","stats","tibble","tidyselect","tools","utf8","utils","vctrs","withr","xfun","xtable","yaml"]},{"type":"character","attributes":{},"value":["1.4.1","4.3.2","0.6.1","1.0.8","1.1.0","2.3.1","3.6.1","2.1-0","1.9.0","4.3.2","4.3.2","0.6.33","1.1.4","0.3.2","0.23","1.0.5","2.1.1","1.1.1","0.5.2","0.1.3","3.4.4","1.6.2","4.3.2","4.3.2","4.3.2","0.3.4","0.10","0.5.7","1.6.4","1.6.13","0.1.4","1.8.7","1.45","0.4.3","1.3.2","0.11.5","1.0.4","2.0.3","1.12","4.3.2","0.12","0.5.0","1.9.0","2.0.3","1.2.1","2.5.1","1.0.11","1.4.3","1.1.2","2.25","2.0.4","0.4.8","1.2.1","1.8.0","4.3.2","3.2.1","1.2.0","4.3.2","1.2.4","4.3.2","0.6.4","2.5.2","0.41","1.8-4","2.3.8"]}]}]}
+{"type":"list","attributes":{"names":{"type":"character","attributes":{},"value":["packages"]}},"value":[{"type":"list","attributes":{"names":{"type":"character","attributes":{},"value":["packages","version"]},"class":{"type":"character","attributes":{},"value":["data.frame"]},"row.names":{"type":"integer","attributes":{},"value":[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62]}},"value":[{"type":"character","attributes":{},"value":["backports","base","bslib","cachem","cellranger","checkmate","cli","colorspace","commonmark","compiler","datasets","digest","ellipsis","evaluate","fansi","farver","fastmap","fontawesome","ggplot2","glue","graphics","grDevices","grid","gtable","highr","htmltools","htmlwidgets","httpuv","jquerylib","jsonlite","knitr","labeling","later","learnr","lifecycle","magrittr","markdown","methods","mime","munsell","pillar","pkgconfig","promises","R6","Rcpp","readxl","rlang","rmarkdown","rprojroot","sass","scales","shiny","stats","tibble","tools","utf8","utils","vctrs","withr","xfun","xtable","yaml"]},{"type":"character","attributes":{},"value":["1.4.1","4.3.1","0.5.1","1.0.8","1.1.0","2.3.1","3.6.1","2.1-0","1.9.0","4.3.1","4.3.1","0.6.33","0.3.2","0.23","1.0.5","2.1.1","1.1.1","0.5.2","3.4.4","1.6.2","4.3.1","4.3.1","4.3.1","0.3.4","0.10","0.5.7","1.6.2","1.6.13","0.1.4","1.8.7","1.45","0.4.3","1.3.2","0.11.5","1.0.3","2.0.3","1.12","4.3.1","0.12","0.5.0","1.9.0","2.0.3","1.2.1","2.5.1","1.0.11","1.4.3","1.1.1","2.25","2.0.4","0.4.7","1.2.1","1.8.0","4.3.1","3.2.1","4.3.1","1.2.3","4.3.1","0.6.4","3.0.0","0.41","1.8-4","2.3.7"]}]}]}
</script>
<!--/html_preserve-->
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