Stat. 450 Section 1 or 2: Homework 4

Prof. Eric A. Suess

So how should you complete your homework for this class?

• First thing to do is type all of your information about the problems you do in the text part of your R Notebook.
• Second thing to do is type all of your R code into R chunks that can be run.
• If you load the tidyverse in an R Notebook chunk, be sure to include the “message = FALSE” in the {r}, so {r message = FALSE}.
• Last thing is to spell check your R Notebook. Edit > Check Spelling… or hit the F7 key.

Homework 4:

 Read: Chapter 5
 Do 5.4.1 Exercise 4
 Do 5.5.2 Exericise 1, 4
 Do 5.6.7 Exercise 1

library(tidyverse)

5.4.1

4.

Yes. The contains() helper function picks out all of the variables in the dataset that contains the word TIME. The function is also not case sensitive.

library(nycflights13)
flights

flights %>% select(contains("TIME"))

The select() helpers are not case sensitive, when R is case sensitive.

To change the default. Don’t know why it does not show the columns like above.

flights %>% select(contains("TIME", ignore.case = FALSE))

5.5.2

1.

Minutes since midnight.

flights 

Covert dep_time and sechedule_dep_time to minutes since midnight.

dep_time %/% 100 * 60 This give the minutes since midnight.

dep_time %% 100 This gives the reminder in minutes.

flights %>% mutate(dep_time_mins = ( ( (dep_time %/% 100) * 60 ) + (dep_time %% 100)),
                   sched_dep_time_mins = ( ( (sched_dep_time %/% 100) * 60 ) + (sched_dep_time %% 100))  )

4.

Ten most delayed flights. There are no ties in these 10.

flights %>% arrange(desc(dep_delay)) %>%
  head(10)

5.6.7

1.

Brainstorm at least 5 different ways to assess the typical delay characteristics of a group of flights.

1. median and mean of dep_delay time in minutes.
2. sd of dep_delay time in minites
3. median and mean of arr_delay time in minutes.
4. sd of dep_delay time in minutes
5. is the distribution of arr_delay symmetric or skewed? Same questions for dep_delay?

Which is more important: arrival delay or departure delay?

Arrival delay is more important.

What proportion of flights are on time or arrive early? Approximtely 60% of all flights are on time.

flights %>% summarize(flt_ontime = mean(arr_delay <= 0, na.rm = TRUE) )

Which arrier/airline has the best ontime rate?

flights %>% group_by(carrier) %>%
  summarize(flt_ontime = mean(arr_delay <= 0, na.rm = TRUE) ) %>%
  arrange(flt_ontime)

What proportion of flight are 10 mins or more late?

flights %>% summarize(flt_late10 = mean(arr_delay >= 10, na.rm = TRUE) )

flights %>% group_by(carrier) %>%
  summarize(flt_late10 = mean(arr_delay >= 10, na.rm = TRUE) ) %>%
    arrange(flt_late10)

What proportion of flight are 30 mins or more late?

flights %>% summarize(flt_late30 = mean(arr_delay >= 30, na.rm = TRUE) )

flights %>% group_by(carrier) %>%
  summarize(flt_late30 = mean(arr_delay >= 30, na.rm = TRUE) ) %>%
  arrange(flt_late30)