```{r setup, include=FALSE} 
knitr::opts_chunk$set(echo = TRUE) 
library(tidyverse) 
``` 

# Tutorial - 2. Task Set 

## Part 1 of the Task Set 

### Step 1 

Download the file "mdb_data.RDS" from my website, save it in the correct directory, and import it. 
```{r} 

``` 

### Step 2 

How many Members of Parliament have at least one "x" in their surname? 

```{r} 

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### Step 3 

What is the most common first name in the German Parliament (Bundestag)? 
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### Step 4 

Were there more men with the names Wolfgang and Hans in Parliament than women in total? 
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Thank goodness not. 

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### Step 5 

Create a variable containing the year of birth of the Members of Parliament. Which MP was born first? 

```{r} 


``` 

## Part 2 of the Task Set 
### Step 6 - Import of the Text File 

Download the (reduced) corpus of British parliamentary speeches from my website, save it correctly, and import it into the R environment. 
```{r} 

``` 

### Step 7 - Data Insight 

How often did which party speak in the British House of Commons in recent years? Display the number of speech contributions tabularly. 
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...and is there a Gender Gap? 

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### Step 8 - Descriptive Insight into the Text 

Now search for the word "Brexit" and display how often it was used in speeches about Brexit in recent years. 

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!!! CHALLENGE 
Is there a temporal trend? 
Display the development in the frequency of speeches on Brexit graphically. 

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Which party speaks most frequently about Brexit? 
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The graphic distorts a little how significant Brexit is in the parliamentary debate. Calculate a proportional share of Brexit speeches relative to the total volume of parliamentary speeches per party. 

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Compare the frequency of the Brexit debate with the frequency of speeches on Migration. 

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What are the speeches revolving around Brexit about? 
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```