Enter your name and EID here

This is the dataset you will be working with:

members <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-09-22/members.csv')

members_everest <- members %>%
  filter(peak_name == "Everest") %>% # only keep expeditions to Everest
  filter(!is.na(age)) %>%     # only keep expedition members with known age
  filter(year >= 1960)        # only keep expeditions since 1960 

More information about the dataset can be found at https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-09-22/readme.md and https://www.himalayandatabase.com/.

Part 1

Question: Are there age differences for expedition members who were successful or not in climbing Mt. Everest with or without oxygen, and how has the age distribution changed over the years?

We recommend you use a violin plot for the first part of the question and faceted boxplots for the second question part of the question.

Hints:

 + facet_wrap(
    # your other arguments to facet_wrap() go here
    ...,
    # this replaces "TRUE" with "summited" and "FALSE" with "did not summit"
    labeller = as_labeller(c(`TRUE` = "summited", `FALSE` = "did not summit"))
  )

Introduction: Your introduction here.

Approach: Your approach here.

Analysis:

# Your R code here
# Your R code here

Discussion: Your discussion of results here.

Part 2

Question: Your question here.

Introduction: Your introduction here.

Approach: Your approach here.

Analysis:

# Your R code here
# Your R code here

Discussion: Your discussion of results here.