PLG 310 Lab Assingment 1
pdf
keyboard_arrow_up
School
Toronto Metropolitan University *
*We aren’t endorsed by this school
Course
310
Subject
Industrial Engineering
Date
Dec 6, 2023
Type
Pages
8
Uploaded by MinisterAardvarkPerson924
1
Lab 1
Urban and Regional Planning, Toronto Metropolitan University
PLG - 310 : Statistics for Planners
Dr. Yemi Adediji
October 4, 2023
2
Regionid, Region ID : This what region the household is in. Continuous.
Anyvmt, Any Vehicle Miles Traveled : This is if the household had any VMT. Binomial.
Anybike, Any Bike Used : This is if the household had any bike usage. Binomial.
Anytransit, Any Transit Used : This is if the household had any transit usage. Binomial
Htype, Housing Type : This is the type of housing. Nominal.
Hhincome, HouseHold Income : This is the income of the household. Continuous.
Income_cat, Income Category : This is the category of income of the household. Discrete.
Frequency Graph - HouseHold Size
People
Frequency
Relative
Frequency
1
3225
0.25962
2
4777
0.38456
3
1929
0.15529
4
1691
0.13613
5
569
0.04581
6
164
0.01320
7
50
0.00403
8
14
0.00113
9
1
8.05e-5
10
2
1.61e-4
We can see with this frequency table on Household size that 2 people in a household is the most
common. 9 people in a household is the least common. There are a total of 12,444 data points in
this data set.
3
Bar Graph of Household Size
We can see in a bar graph that the mean appears to be 2.39 people per household. The median is
shown to be 2. There is a minimum of 1 and a maximum of 10. There is a standard deviation of
1.26, with a variance of 1.59. There is a difference of 1552 data point between the most common
answer and the second most common.
Histogram of Household Income
Looking at the histogram for household income we can see that the graph skewed to the right
with an almost comb distribution. The highest point lies within 0 - 50 and the lowest lies within
150 - 200.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
4
Frequency Table of Any Bike Use, and Any Vehicle Miles Traveled
Yes
or No
Count
Total
Proportion
Any Bike Use
0
12011
12422
0.967
1
411
12422
0.033
Any Vehicle Miles Traveled
0
679
12413
0.055
1
11734
12413
0.945
We can see the proportion of people using a bike to travel is very low with it being 0.033 of the
total data set. While we can see the proportion of people using a car being very high with 0.945
of the total data set. The contrast between people driving and people using the bike is quite stark.
We can see that the 0.055% of people not driving have a 0.033% to ride a bike instead.
Cross Tabulation of Income Category and Any Vehicle Miles Traveled
Income Category
Any Vehicle Miles Traveled
1
2
3
Total
0
Observed
351
232
96
679
% within column
13.0 %
4.4 %
2.1 %
5.5 %
1
Observed
2357
5002
4375
11734
% within column
87.0 %
95.6 %
97.9 %
94.5 %
Total
Observed
2708
5234
4471
12413
% within column
100.0 %
100.0 %
100.0 %
100.0 %
Looking at this cross tabulation we can see a correlation with income category and any VMT. We
see the lower the income category the higher the percentage of people not driving.
This aligns with my idea that as a person's income is lower they may not be able to afford a car
and therefore cannot drive one. We can see that the highest number of people not driving is in the
income category of 1. And the highest number of people driving is in the income category of 3.
5
Five Number Summary of Household Income
House Hold Income
N
12422
Standard deviation
41.4
Range
194
Minimum
0.00
Maximum
194
25th percentile
36.1
50th percentile
67.1
75th percentile
97.1
Five Number Summary of Household Income By Housing Type
Housing Type
House Hold Income
N
0
181
1
10049
2
868
3
1324
Standard deviation
0
27.5
1
41.2
2
33.6
3
33.3
Minimum
0
2.78
6
1
0.00
2
0.00
3
0.00
Maximum
0
171
1
194
2
194
3
194
25th percentile
0
23.8
1
45.6
2
24.1
3
21.5
50th percentile
0
40.0
1
74.2
2
45.6
3
40.0
75th percentile
0
51.4
1
104
2
67.1
3
62.8
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
7
Box Graph of Household Income by Housing Type
We can see from these graphs that housing type 1 by far has the most data points with 10049
with the next closest being housing type 3 with 1324. With this we can conclude that housing
type 1 is the most common type of housing with the most data sets. Housing type 1 has the
highest standard deviation meaning it has the most varied data. Between quartiles Housing type 0
2 3 are very similar whereas housing type 1 is very different. The results are not what I expected
as seeing such a disproportionate number of data points for housing type 1 was surprising.
8
References
The jamovi project (2022). jamovi. (Version 2.3) [Computer Software]. Retrieved from
https://www.jamovi.org.
R Core Team (2021). R: A Language and environment for statistical computing. (Version 4.1)
[Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved
from MRAN snapshot 2022-01-01).