Introduction

Today’s dataset consists of over two-thousand records from the sinking of the RMS Titanic, a disaster faithfully depicted with a very high degree of historical accuracy in James Cameron’s 1997 film*. On a cold April morning, the RMS Titanic struck an iceberg in the North Atlantic, broke apart and sank (spoiler warning), resulting in a tremendous loss of life.

On the Titanic, passengers were either first class, second class, or third class, depending on the ticket they purchased. It is well known that survival probability after the sinking depended on the passenger’s ticket class: over 60% of the first class passengers survived, whereas only about 25% of the third class passengers survived (contrary to the film’s depiction, there is no evidence that they were “locked in” below decks).

However, it appears that the crew fared even worse! Of the crewmembers, less than a quarter of them made it out alive. Does this information lead us to make conclusions one way or another regarding survival probability of third class passengers compared to crewmembers?

Merge Conflicts (uh oh)

You may have seen this already through the course of your collaboration last week in Lab 03. When two collaborators make changes to a file and push the file to their repository, git merges these two files.

If these two files have conflicting content on the same line, git will produce a merge conflict. Merge conflicts generally need to be resolved manually, as they require a human intervention:

To resolve the merge conflict, decide if you want to keep only your text, the text on GitHub, or incorporate changes from both texts. Delete the conflict markers <<<<<<<, =======, >>>>>>> and make the changes you want in the final merge.

Assign numbers 1, 2, 3, and 4 to each of your team members (if you have 3 team members, just numbers 1 through 3). Go through the following steps in detail, which simulate a merge conflict. Completing this exercise will be part of the lab grade.

Resolving a merge conflict

Step 1: Everyone clone your assignment repo into RStudio Cloud and open the R Markdown file. Don’t forget to load in the necessary packages and configure git:

library(tidyverse) 
library(usethis)
use_git_config(user.name="your name", user.email="your email")

Member 4 should look at the group’s repo on GitHub.com to ensure that the other members’ files are pushed to GitHub after every step.

Step 2: Member 1 Change the team name to your team name. Knit, stage, commit, and push.

Step 3: Member 2 Change the team name to something different (i.e., not your team name). Knit, stage, commit, and push.

You should get an error.

Pull and review the document with the merge conflict. Show the error to your teammates. A merge conflict occurred because you edited the same part of the document as Member 1. Resolve the conflict with whichever name you want to keep, then knit, stage, commit and push again.

Step 4: Member 3 Write some narrative in the space provided for Exercise 5, then knit, commit, and push.

You should get an error.

This time, no merge conflicts should occur, since you edited a different part of the document from Members 1 and 2. Show the error to your teammates, then pull. Finally, knit, commit, and push.

Caching GitHub credentials

If you would like your git password cached for a week for this project, type the following in the Terminal:

git config --global credential.helper 'cache --timeout 604800'

You will need to enter your GitHub username and password one more time after caching the password. After that you won’t need to enter your credentials for 604800 seconds = 7 days. Note that this is only good for this single RStudio Cloud project – you will need to cache your credentials for each project you create.

The data

The data may be loaded with the following code:

titanic <- read_csv("data/titanicsurvival.csv")

Exercises

Write all R code according to the style guidelines discussed in class. Be especially careful about staying within the 80 character limit, as demonstrated by your lab TAs! Finally, make sure your team name is correct. Only one submission should be made per team.

All team members must commit and push to receive full credit

What does each observation represent in this dataset? How many variables are in this dataset? What type of variable is each?
Summarize the proportion of surviving passengers who survived in each class. What are the conditional probabilities of survival for each of the passenger classes, and among crewmembers?
Create a data visualization that examines overall survival probability of third-class passengers compared to crew members. Do not include information regarding first or second class passengers; we are not interested in them!
You suspect that there is a case of Simpson’s paradox going on. Recreate your visualization from Exercise 3, this time faceting by categories of a third variable.
What changed, and what might explain this change? Explain the relationship between the three variables in your visualization from Exercise 4 and what you might conclude.