assignment4.Rmd

---
title: "Statistical assignment 4"
author: "[add your name here] [add your candidate number here - mandatory]"
date: "[add date here]"
output: github_document
---

```{r setup, include=FALSE}
# Please note these options.
# This tells R Markdown that we want to show code in the output document.
knitr::opts_chunk$set(echo = TRUE)
# Switching off messages in the output document. 
knitr::opts_chunk$set(message = FALSE)
knitr::opts_chunk$set(warning = FALSE)
# Switching on caching to make things faster (don't commit cache files on Github).
knitr::opts_chunk$set(cache = TRUE)
```

In this assignment you will need to reproduce 5 ggplot graphs. I supply graphs as images; you need to write the ggplot2 code to reproduce them and knit and submit a Markdown document with the reproduced graphs (as well as your .Rmd file).

First we will need to open and recode the data. I supply the code for this; you only need to change the file paths.

    ```{r}
library(tidyverse)
Data8 <- read_tsv("...h_indresp.tab")

Data8 <- Data8 %>%
        select(pidp, h_age_dv, h_payn_dv, h_gor_dv)

Stable <- read_tsv("...xwavedat.tab")

Stable <- Stable %>%
        select(pidp, sex_dv, ukborn, plbornc)

Data <- Data8 %>% left_join(Stable, "pidp")

rm(Data8, Stable)

Data <- Data %>%
        mutate(sex_dv = ifelse(sex_dv == 1, "male",
                           ifelse(sex_dv == 2, "female", NA))) %>%
        mutate(h_payn_dv = ifelse(h_payn_dv < 0, NA, h_payn_dv)) %>%
        mutate(h_gor_dv = recode(h_gor_dv,
                         `-9` = NA_character_,
                         `1` = "North East",
                         `2` = "North West",
                         `3` = "Yorkshire",
                         `4` = "East Midlands",
                         `5` = "West Midlands",
                         `6` = "East of England",
                         `7` = "London",
                         `8` = "South East",
                         `9` = "South West",
                         `10` = "Wales",
                         `11` = "Scotland",
                         `12` = "Northern Ireland")) %>%
        mutate(placeBorn = case_when(
                ukborn  == -9 ~ NA_character_,
                ukborn < 5 ~ "UK",
                plbornc == 5 ~ "Ireland",
                plbornc == 18 ~ "India",
                plbornc == 19 ~ "Pakistan",
                plbornc == 20 ~ "Bangladesh",
                plbornc == 10 ~ "Poland",
                plbornc == 27 ~ "Jamaica",
                plbornc == 24 ~ "Nigeria",
                TRUE ~ "other")
        )

    ```

Reproduce the following graphs as close as you can. For each graph, write two sentences (not more!) describing its main message.

(Note the position of the code chunks; each is preceded by four spaces. This helps display numbered lists correctly in the Markdown file with the output.)

1. Histogram (20 points)

    ```{r}

         
    ```

2. Scatter plot (20 points). The red line shows a linear fit; the blue line shows a quadratic fit. Note the size and position of points.

    ```{r}

    ```

3. Faceted density chart (20 points).

    ```{r}

    ```

4. Ordered bar chart of summary statistics (20 points).

    ```{r}

    ```

5. Map (20 points). This is the most difficult problem in this set. You will need to use the NUTS Level 1 shape file (available here -- https://data.gov.uk/dataset/2aa6727d-c5f0-462a-a367-904c750bbb34/nuts-level-1-january-2018-full-clipped-boundaries-in-the-united-kingdom) and a number of packages for producing maps from shape files. You will need to google additional information; there are multiple webpages with the code that produces similar maps.

    ```{r}

    ```