Intro to Stats questions answered
Need the questions answered from the data given.
AirBnBData
Neighborhood Room Type Price/Night Min. Nights # Reviews Reviews/Mo. # Host Listings Days Available
Central Area Entire home/apt 296 7 29 0.21 2 59
Delridge Entire home/apt 48 3 462 3.92 1 0
Other neighborhoods Entire home/apt 90 2 150 1.19 3 49
Other neighborhoods Private room 62 2 146 1.29 8 359
Downtown Private room 99 3 455 3.65 4 138
West Seattle Entire home/apt 165 3 39 0.41 2 336
West Seattle Entire home/apt 125 2 46 0.48 2 346
Other neighborhoods Entire home/apt 120 2 93 0.91 3 0
West Seattle Entire home/apt 125 3 73 0.6 8 347
Other neighborhoods Entire home/apt 299 2 91 0.76 3 177
Other neighborhoods Private room 40 2 145 1.28 3 293
Other neighborhoods Private room 60 1 71 0.7 3 173
Other neighborhoods Private room 32 21 21 0.21 2 179
West Seattle Entire home/apt 105 2 121 1.05 8 171
Downtown Entire home/apt 170 2 105 0.94 58 144
Ballard Entire home/apt 89 2 569 4.98 2 133
Ballard Entire home/apt 79 2 322 5.93 2 127
Downtown Entire home/apt 206 1 93 0.84 58 155
Ballard Entire home/apt 70 2 778 6.67 1 147
Capitol Hill Entire home/apt 259 2 143 1.28 1 0
Cascade Entire home/apt 165 3 63 0.56 1 358
Ballard Entire home/apt 64 3 118 1.03 1 0
Ballard Entire home/apt 85 2 3 0.08 2 340
Beacon Hill Entire home/apt 95 10 28 0.25 1 203
Other neighborhoods Private room 55 2 272 2.41 1 344
Other neighborhoods Private room 50 30 47 0.42 4 137
Other neighborhoods Entire home/apt 80 5 43 0.39 2 139
Other neighborhoods Private room 45 3 30 0.27 4 355
Other neighborhoods Entire home/apt 75 2 250 3.99 1 349
Ballard Entire home/apt 76 3 239 2.29 1 333
Other neighborhoods Private room 50 3 28 0.26 4 172
Other neighborhoods Private room 45 3 29 0.27 4 355
Seward Park Private room 70 2 189 1.78 1 352
Capitol Hill Entire home/apt 149 30 0 3 108
Capitol Hill Entire home/apt 110 5 15 0.14 1 0
Capitol Hill Entire home/apt 95 1 10 2.17 1 86
West Seattle Private room 75 2 72 0.69 1 364
West Seattle Entire home/apt 92 2 163 1.57 1 261
Northgate Entire home/apt 120 2 227 2.22 1 38
Beacon Hill Entire home/apt 130 2 63 0.61 1 270
Other neighborhoods Entire home/apt 120 30 52 0.51 1 94
West Seattle Private room 150 2 138 1.37 2 360
Other neighborhoods Entire home/apt 79 3 390 3.8 2 358
Other neighborhoods Entire home/apt 110 2 120 1.17 1 303
Other neighborhoods Entire home/apt 150 3 278 2.75 2 170
Capitol Hill Entire home/apt 170 7 176 1.76 13 182
Seward Park Private room 85 2 80 1.04 2 354
Central Area Entire home/apt 135 2 86 1.24 2 90
Central Area Private room 75 1 149 1.45 1 344
Beacon Hill Private room 89 2 384 3.75 1 353
Central Area Entire home/apt 68 3 384 3.75 1 342
Capitol Hill Entire home/apt 199 3 42 0.41 3 38
Queen Anne Entire home/apt 750 2 247 2.44 1 288
Queen Anne Entire home/apt 250 3 1 0.01 1 0
West Seattle Entire home/apt 78 2 310 3.1 1 129
Rainier Valley Entire home/apt 80 2 157 2.33 2 0
West Seattle Private room 59 1 102 2.28 2 90
West Seattle Entire home/apt 89 1 195 1.94 1 116
Other neighborhoods Entire home/apt 175 30 25 0.39 1 310
Other neighborhoods Entire home/apt 99 30 143 1.43 1 0
Other neighborhoods Private room 95 3 73 1.1 4 173
Rainier Valley Entire home/apt 80 2 373 3.81 1 76
Downtown Entire home/apt 200 2 169 1.72 4 240
Ballard Private room 90 1 132 1.46 2 171
Other neighborhoods Entire home/apt 280 3 87 0.95 4 172
Downtown Entire home/apt 139 1 109 1.15 4 346
Ballard Entire home/apt 175 3 92 1 4 293
Magnolia Private room 46 1 211 2.16 2 361
Other neighborhoods Private room 55 2 156 1.59 8 364
West Seattle Entire home/apt 285 3 11 0.64 2 339
Lake City Private room 54 3 163 1.65 1 357
West Seattle Private room 60 1 1 0.01 1 324
Queen Anne Entire home/apt 215 2 114 1.57 3 193
Queen Anne Entire home/apt 165 3 299 3.05 3 79
Other neighborhoods Entire home/apt 125 7 4 0.04 1 90
West Seattle Entire home/apt 85 1 242 2.47 1 353
Other neighborhoods Entire home/apt 85 30 161 1.66 1 79
Ballard Entire home/apt 100 1 57 0.61 1 293
Other neighborhoods Entire home/apt 200 4 31 0.34 2 24
Other neighborhoods Entire home/apt 195 2 0 1 0
Downtown Entire home/apt 206 2 77 0.88 58 149
Downtown Entire home/apt 139 2 127 1.31 4 254
Queen Anne Entire home/apt 400 3 73 0.81 3 240
Ballard Entire home/apt 150 2 2 0.05 1 0
Central Area Entire home/apt 229 7 165 1.75 13 177
Capitol Hill Private room 99 1 53 0.56 6 0
Downtown Entire home/apt 183 3 196 2.08 1 321
Downtown Entire home/apt 182 2 102 1.06 58 149
Capitol Hill Entire home/apt 125 7 51 0.66 1 141
Downtown Entire home/apt 160 2 60 0.64 58 137
Cascade Entire home/apt 120 30 10 0.1 2 353
Cascade Private room 50 1 4 0.05 2 0
Capitol Hill Entire home/apt 240 7 183 2.03 13 180
Central Area Entire home/apt 135 5 5 0.05 1 0
Capitol Hill Entire home/apt 165 1 120 1.3 3 365
Other neighborhoods Entire home/apt 90 2 193 2.06 1 129
Central Area Entire home/apt 500 30 55 1.21 3 0
Downtown Entire home/apt 155 30 54 0.6 6 171
West Seattle Entire home/apt 107 4 70 0.75 1 50
West Seattle Entire home/apt 185 4 37 0.4 1 264
Mean 136.24 5.32 134.22 1.44 5.37 192.25
Std. Deviation 99.55 8.17 132.61 1.29 12.38 127.53
Minimum 32.00 1.00 0.00 0.01 1.00 0.00
Q1 78.75 2.00 45.25 0.56 1.00 90.00
Median 108.50 2.00 97.50 1.13 2.00 172.50
Q3 166.25 3.00 170.75 2.01 3.25 336.75
Maximum 750.00 30.00 778.00 6.67 58.00 365.00 Math&146 | Optional Project
DUE: Monday, March 16th
Name: _________________________________________________
Analyzing AirBnB Data
Introduction
In the module in Canvas where you found this document, you will also find the file AirBnBData.xlsx. You will need that
dataset to complete this project. Follow the instructions on this worksheet to complete the project. The project is due
Monday, August 17th. It is optional, but can improve your exam score if you choose to complete it.
The Data
AirBnB allows much of their data to be viewed publicly and the website Inside AirBnB
(http://insideairbnb.com/index.html) does a good job compiling and releasing the data for many cities around the world.
One city they release data for is Seattle. The data you find in this module is a random selection of 100 AirBnB Listings in
Seattle in 2019 (there are over 8000 listings, so I went ahead and selected 100 for you).
I have cleaned up the data a bit, and labeled the variables measured. There are a total of eight variables measured for
each listing, and they are as follows:
Neighborhood: Describes the neighborhood within Seattle that a listing is located in.
Room Type: Describes the type of rental, which can either be a single room within a larger dwelling, or an entire
house/apartment.
Price/Night: Describes the average price charged per night for each listing.
Min. Nights: Describes the minimum nights required to make a reservation at each listing. Some rentals require
guests to reserve more than one night at a time.
# Review: Describes how many total reviews have been submitted for each listing.
Reviews/Mo.: Describes, on average, how many reviews were submitted each month for each listing.
# Host Listing: Describes how many listings each listing person hosts on AirBnB. Some people/companies list
more than one rental on AirBnB.
Days Available: Describes how many days each listing was available to be rented out during the year of 2019.
You will notice at the end of each column for all of the quantitative (numerical) variables I have provided summary
statistics consisting of the: sample mean, sample standard deviation, and the five-number summary. You will need these
values to complete this project.
The Project
Answer the following questions and fill in each part to perform a robust data analysis using the skills you have developed
throughout the first 8 modules of this course. Use complete sentenced when appropriate, and show all work to receive
full credit.
1.) [10 pts] The data set contains both qualitative (categorical) and quantitative (numerical) variables. Identify each of
the eight variables from the dataset as either qualitative or quantitative by listing each one under one of the
categories below.
Qualitative Variables Quantitative Variables
2.) For this part, choose only one of the qualitative variables from the dataset to analyze.
a.) [1 pt] Which of the qualitative variables did you choose to analyze?
b.) [4 pts] Create a relative frequency distribution that summarizes the qualitative variable.
c.) [5 pts] Create an appropriate graph that displays the qualitative variable you chose to analyze. Graphing by hand
is just fine, but you are welcome to use any software you would like to create the graph.
d.) [2 pts] For the qualitative variable you chose pick one of the possible values of the variable and calculate , the
sample proportion of listings that have the value you chose (Example: if I was analyzing the Neighborhood
variable, I could calculate the proportion of listings that were in Ballard). Hint: You already calculate sample
proportions in part (b.)!
Value you picked: ____________________ =_______________
e.) [10 pts] Use your from part (d.) and calculate a 90% confidence interval for the true proportion of listings that
have the value you chose (Example: if I calculated the proportion of listings in Ballard in part (d.), I would be
constructing a 90% confidence interval for the true proportion of listings that were in Ballard).
f.) [3 pts] Interpret your 90% confidence interval
3.) For this part, choose only one of the quantitative variables from the dataset to analyze.
a.) [1 pt] Which of the quantitative variables did you choose to analyze?
b.) [4 pts] Create a frequency distribution/table that summarizes the quantitative variable.
c.) [5 pts] Create a histogram that displays the qualitative variable you chose to analyze. Graphing by hand is just
fine, but you are welcome to use any software you would like to create the graph.
d.) [2 pts] Based on your graph, how would you describe the shape of the distribution of the variable?
e.) [3 pts] For the variable you selected, compare the mean to the median (both found at the bottom of the
dataset). How do they compare? Does this seem reasonable given the shape of the dataset you found in your
graph?
(3 continued)
f.) [5 pts] For the quantitative variable you selected, use the 5-Number Summary (found at the bottom of the
dataset) to test for any outliers. Are there any outliers within the dataset for the variable you chose to analyze?
g.) [10 pts] For the quantitative variable you have chosen to analyze, use the sample mean and sample standard
deviation (both found at the bottom of the dataset) to construct a 95% confidence interval for the true mean
value of the variable.
h.) [3 pts] Interpret your 95% confidence interval.
i.) [2 pts] Did you find anything particularly interesting or noteworthy about the variable you chose to analyze?
What kind of takeaways could you give someone about the quantitative variable you chose to analyze if they
were not familiar with the dataset or statistics in general?
