Sebastian Sauer sebastiansauer

## multiple_tabulate.R
library(dplyr)
data(Wage, package = "ISLR")


Wage %>%
  mutate(wage_f = ntile(wage, 2)) %>%  # bin it
  group_by(wage_f, health, race) %>%
  summarise(count = n()) %>%
  ggplot(aes(x = factor(wage_f), y = count, fill = race)) +
  geom_bar(stat = "identity") +

## tips_Analyse.R
###############################################################################
### Beispiel-Analyse des Datensatzes "tips"
### von Sebastian Sauer, letztes Update: 2016-01-18
### Zugang zu den Daten: Der Datensatz findet sich im Paket "reshape2"
###############################################################################

# Hinweis: Es ist ganz normal, Syntax/Befehle nachzuschlagen :)
# Eine Möglichkeit dazu ist mit help(Befehl), z.B.
help(library)  # oder mit google :)

## DiagrammeR_Example.R
# Plot path diagram with {DiagrammeR}

data(Wage, package = "ISLR")  #load data


lm_wage <- lm(wage ~ health + age + health:age, data = Wage)  # run linear model
summary(lm_wage)

library(semPlot)  # plot path diagram with {semPlot}
semPaths(lm_wage,  whatLabel = "est", vsize.man = 16, edge.label.cex=0.6)

## README.md

      
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                sebastiansauer
                / README.md
            
            
              Created
              June 21, 2017 15:12
                — forked from hofmannsven/README.md
            
              
                My simply Git Cheatsheet
              
          
    Using Git

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Related Setup: https://gist.github.com/hofmannsven/6814278
Related Pro Tips: https://ochronus.com/git-tips-from-the-trenches/

  
## election.csv

          
            afd_votes
            votes_total
            foreigner_n

            
              11647
              170396
              16100

            
              9023
              138075
              12600

            
              11176
              130875
              11000

            
              11578
              156268
              9299

            
              10390
              150173
              25099

            
              11161
              130514
              13000

            
              15977
              186372
              26000

            
              17166
              191937
              18300

            
              11780
              137273
              9400

## election_data.csv
state,area_nr,area_name,total_n,germans_n,foreigner_n,pop_move_n,pop_migr_background_n,income,unemp_n,votes_total,afd_votes,afd_prop,east,state_id,total_n_z,germans_n_z,foreigner_n_z,pop_move_n_z,pop_migr_background_n_z,income_z,unemp_n_z,votes_total_z,afd_votes_z,afd_prop_z
Schleswig-Holstein,1,Flensburg – Schleswig,282800,266700,16100,3478440,28280,20265,20361,170396,11647000,0.06835254348693631,0,15,0.2103609895241015,0.7384953705950867,-0.6866607746103975,-0.23405819513595597,-0.8241784980071718,-0.331229037339419,0.5294325736242255,0.7420571802149715,-0.9559380206641114,-1.0844472782356187
Schleswig-Holstein,2,Nordfriesland – Dithmarschen Nord,232300,219700,12600,3066360,18584,22159,16725,138075,9023000,0.06534854245880861,0,15,-1.12317180392684,-0.9301927624096695,-0.8739260711324136,-0.5246213450924033,-1.1451159729868976,0.4782205523605706,-0.0022599637360526327,-0.8725210301240619,-1.2691398862049443,-1.1394454488402648
Schleswig-Holstein,3,Steinburg – Dithmarschen Süd,220800,209800,11000,2627520,203

## logistic_curve.R

library(ggplot2)
# library(cowplot)
library(dplyr)

logist <- function(x){
  y = exp(x) / (1 + exp(x))
}

p1 <- ggplot(data_frame())

## testing.log
This is pdfTeX, Version 3.14159265-2.6-1.40.20 (TeX Live 2019) (preloaded format=pdflatex 2020.1.13)  28 JAN 2020 11:54
entering extended mode
 restricted \write18 enabled.
 %&-line parsing enabled.
**testing.tex
(./testing.tex
LaTeX2e <2019-10-01> patch level 3

(/Users/sebastiansaueruser/Library/TinyTeX/texmf-dist/tex/latex/beamer/beamer.c
ls

## extract_solutions.R

extract_solutions <- function(file) {

  require(tidyverse)

  # input:
  # file: the output file from the exam2nops call storing the exams meta info

  # output:
  # list of solutions for each exam variant and each question

## nops_grading.Rmd
---
title: "Grading BDA WS20"
author: "Sebastian Sauer"
date: "2/5/2021"
output: html_document
---

```{r global-knitr-options, include=FALSE}
knitr::opts_chunk$set(fig.pos = 'H',
                      fig.asp = 0.618,
	library(dplyr)
	data(Wage, package = "ISLR")


	Wage %>%
	mutate(wage_f = ntile(wage, 2)) %>% # bin it
	group_by(wage_f, health, race) %>%
	summarise(count = n()) %>%
	ggplot(aes(x = factor(wage_f), y = count, fill = race)) +
	geom_bar(stat = "identity") +
	###############################################################################
	### Beispiel-Analyse des Datensatzes "tips"
	### von Sebastian Sauer, letztes Update: 2016-01-18
	### Zugang zu den Daten: Der Datensatz findet sich im Paket "reshape2"
	###############################################################################

	# Hinweis: Es ist ganz normal, Syntax/Befehle nachzuschlagen :)
	# Eine Möglichkeit dazu ist mit help(Befehl), z.B.
	help(library) # oder mit google :)
	# Plot path diagram with {DiagrammeR}

	data(Wage, package = "ISLR") #load data


	lm_wage <- lm(wage ~ health + age + health:age, data = Wage) # run linear model
	summary(lm_wage)

	library(semPlot) # plot path diagram with {semPlot}
	semPaths(lm_wage, whatLabel = "est", vsize.man = 16, edge.label.cex=0.6)
afd_votes	votes_total	foreigner_n
11647	170396	16100
9023	138075	12600
11176	130875	11000
11578	156268	9299
10390	150173	25099
11161	130514	13000
15977	186372	26000
17166	191937	18300
11780	137273	9400
	state,area_nr,area_name,total_n,germans_n,foreigner_n,pop_move_n,pop_migr_background_n,income,unemp_n,votes_total,afd_votes,afd_prop,east,state_id,total_n_z,germans_n_z,foreigner_n_z,pop_move_n_z,pop_migr_background_n_z,income_z,unemp_n_z,votes_total_z,afd_votes_z,afd_prop_z
	Schleswig-Holstein,1,Flensburg – Schleswig,282800,266700,16100,3478440,28280,20265,20361,170396,11647000,0.06835254348693631,0,15,0.2103609895241015,0.7384953705950867,-0.6866607746103975,-0.23405819513595597,-0.8241784980071718,-0.331229037339419,0.5294325736242255,0.7420571802149715,-0.9559380206641114,-1.0844472782356187
	Schleswig-Holstein,2,Nordfriesland – Dithmarschen Nord,232300,219700,12600,3066360,18584,22159,16725,138075,9023000,0.06534854245880861,0,15,-1.12317180392684,-0.9301927624096695,-0.8739260711324136,-0.5246213450924033,-1.1451159729868976,0.4782205523605706,-0.0022599637360526327,-0.8725210301240619,-1.2691398862049443,-1.1394454488402648
	Schleswig-Holstein,3,Steinburg – Dithmarschen Süd,220800,209800,11000,2627520,203

	library(ggplot2)
	# library(cowplot)
	library(dplyr)

	logist <- function(x){
	y = exp(x) / (1 + exp(x))
	}

	p1 <- ggplot(data_frame())
	This is pdfTeX, Version 3.14159265-2.6-1.40.20 (TeX Live 2019) (preloaded format=pdflatex 2020.1.13) 28 JAN 2020 11:54
	entering extended mode
	restricted \write18 enabled.
	%&-line parsing enabled.
	**testing.tex
	(./testing.tex
	LaTeX2e <2019-10-01> patch level 3

	(/Users/sebastiansaueruser/Library/TinyTeX/texmf-dist/tex/latex/beamer/beamer.c
	ls

	extract_solutions <- function(file) {

	require(tidyverse)

	# input:
	# file: the output file from the exam2nops call storing the exams meta info

	# output:
	# list of solutions for each exam variant and each question
	---
	title: "Grading BDA WS20"
	author: "Sebastian Sauer"
	date: "2/5/2021"
	output: html_document
	---

	```{r global-knitr-options, include=FALSE}
	knitr::opts_chunk$set(fig.pos = 'H',
	fig.asp = 0.618,