1.2 Exercises

Exercise 1.2.1

The following dataset contains information about human characters in the Star Wars original trilogy.

name	height	mass	hair_color	eye_color	age	gender	homeworld	from_tatooine
Luke Skywalker	172	77.0	blond	blue	19.0	masculine	Tatooine	1
Darth Vader	202	136.0	none	yellow	41.9	masculine	Tatooine	1
Leia Organa	150	49.0	brown	brown	19.0	feminine	Alderaan	0
Owen Lars	178	120.0	brown	blue	52.0	masculine	Tatooine	1
Beru Whitesun Lars	165	75.0	brown	blue	47.0	feminine	Tatooine	1
Biggs Darklighter	183	84.0	black	brown	24.0	masculine	Tatooine	1
Obi-Wan Kenobi	182	77.0	auburn	blue-gray	57.0	masculine	Stewjon	0
Wilhuff Tarkin	180		auburn	blue	64.0	masculine	Eriadu	0
Han Solo	180	80.0	brown	brown	29.0	masculine	Corellia	0
Wedge Antilles	170	77.0	brown	hazel	21.0	masculine	Corellia	0
Palpatine	170	75.0	grey	yellow	82.0	masculine	Naboo	0
Boba Fett	183	78.2	black	brown	31.5	masculine	Kamino	0
Lando Calrissian	177	79.0	black	brown	31.0	masculine	Socorro	0
Lobot	175	79.0	none	blue	37.0	masculine	Bespin	0
Mon Mothma	150		auburn	blue	48.0	feminine	Chandrila	0
Arvel Crynyd			brown	brown		masculine
Raymus Antilles	188	79.0	brown	brown		masculine	Alderaan	0

Use this dataset to calculate summaries to answer the following questions:

Continue to reference the Star Wars data to answer the following questions:

What is the average height (in centimeters) of Star Wars characters?
What is the average weight (in kilograms) of Star Wars characters?
What is the average age of Star Wars characters?
What is the mean of the from_tatooine variable? What does this number tell you?

The following chart shows the values of the height variable from the Star Wars dataset on a number line:

We would call this variable:

(a) Skewed right

(b) Skewed left

The following chart shows the values of the age variable from the Star Wars dataset on a number line:

We would call this variable:

(a) Skewed right

(b) Skewed left

The Star Wars dataset contains only information about human characters. However, these movies also contain many aliens and robots. One of the aliens is a large sluglike character named “Jabba the Hutt”:

name	height	mass	hair_color	eye_color	age	gender	homeworld	from_tatooine
Jabba Desilijic Tiure	175	1358		orange	600	masculine	Nal Hutta	0

How do the means and medians of the height, mass, and age variables change when you include Jabba in the data?

The Star Wars dataset contains all the named human characters from the original movies. If we consider this dataset to be a representative sample, what would be the best description of the population.
1. All characters, human or not, in the original trilogy.
2. All human characters that the creators of Star Wars could have invented for the movies.
3. All characters from science fiction movies that are human.
4. All the human characters who appear in any of the nine Star Wars movies, not just the original trilogy.

Recall the flights dataset from Exercises 1.1. The first few rows of the dataset are shown here:

year	month	day	dep_time	sched_dep_time	dep_delay	arr_time	sched_arr_time	arr_delay	carrier	flight	tailnum	origin	dest	air_time	distance	hour	minute	time_hour
2013	1	1	517	515	2	830	819	11	UA	1545	N14228	EWR	IAH	227	1400	5	15	2013-01-01 05:00:00
2013	1	1	533	529	4	850	830	20	UA	1714	N24211	LGA	IAH	227	1416	5	29	2013-01-01 05:00:00
2013	1	1	542	540	2	923	850	33	AA	1141	N619AA	JFK	MIA	160	1089	5	40	2013-01-01 05:00:00
2013	1	1	544	545	-1	1004	1022	-18	B6	725	N804JB	JFK	BQN	183	1576	5	45	2013-01-01 05:00:00
2013	1	1	554	600	-6	812	837	-25	DL	461	N668DN	LGA	ATL	116	762	6	0	2013-01-01 06:00:00
2013	1	1	554	558	-4	740	728	12	UA	1696	N39463	EWR	ORD	150	719	5	58	2013-01-01 05:00:00

For each of the following quantities, state whether it is a parameter or a statistic:
- The average of the numbers in the air_time column.
- The true average departure delay of United flights from NYC.
- The probability that a flight from EWR will arrive late.
- The proportion of flights in this dataset that were international.
- The average air time of a flight from LGA to LAX.
- The number of observed flights in 2013 that took more than 5 hours.
- How late we should expect our flight to be if we fly from JFK to ATL in December.
- The percentage of flights from the NYC area that will turn out, in the long run, to arrive late.
For each of the following research questions, state the parameter that would best answer the question. This answer will be a sentence describing one or more unknown quantities, such as “The probability that Maria wins her next game of Super Sisters.”
- Should I fly out of LGA airport or JFK airport, if I want to arrive at SFO on time?
- How long does it take to fly from New York to San Francisco?
- Are flights more likely to have takeoff be delayed in the Winter months (Dec-Feb) than in the Summer months (June-August)?
For the three research questions above, describe how you would calculate a statistic from the nycflights13 dataset to estimate that parameter. (You do not have to actually calculate the statistic; only describe your process, like “I would calculate the median of the hour variable.”)