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Welcome back. Hopefully, you enjoyed creating sketches to help determine the story we’ll be communicating to our users. Let’s take a look at my solutions.
Completed Sketches
Vocabulary
- Choropleth map: a map created by coloring in existing geographic regions based on the relative frequency of a variable.
- Scatter plot: a chart that displays the values of two different variables as points so we can study the correlation between the variables.
- Outliers: data points that don’t fit the general pattern.
- Line chart: a chart that shows the change of data over a continuous time span. Line charts show trends or changes in value.
- Pie chart: A circular graph showing how a total amount is divided into parts. The size of each slice indicates a proportion of the whole.
Resources
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Welcome back.
0:00
Hopefully you enjoyed creating sketches
to help determine the story we'll be
0:01
communicating to our users.
0:06
Let's take a look at my solutions.
0:07
In my first sketch, I drew a choropleth
map in which darker values
0:11
represent higher rates of
death per 100,000 population.
0:15
I wanted to sketch quickly, so I drew only
the western half of the United States.
0:20
In this map, a state like New Mexico
with 20.2 deaths per 100,000
0:25
people would be much darker in color
than a state like Utah with only 7.7.
0:31
Note that choropleth maps are meaningful
only when working with relative data.
0:37
While Texas, California, and Florida
had the most auto fatalities in 2019,
0:42
these are also the three most populous
states, so there are a lot more drivers.
0:48
For my second sketch, I was curious
whether there was a correlation between
0:54
the top highway speed in each state versus
the rates of death per 100,000 people.
0:58
To calculate this correlation,
1:04
I used the list of maximum speed
limits from the same IIHS website.
1:07
Using these two data sources, I sketched
out a rough scatter plot to test this out.
1:12
Looking over my sketch, what words would
you use to describe the correlation?
1:18
I would say it's positive,
linear, and quite weak.
1:25
Even though Hawaii has the slowest
highway speeds in America,
1:30
there are quite a few states with
lower auto fatality rates for 2019.
1:34
And look at the states with maximum
70 miles per hour speed limits.
1:39
The death rate varies from 6.5 in
Minnesota to 21.6 in Mississippi.
1:44
So this particular chart contains too
many outliers to convincingly demonstrate
1:50
a correlation between top highway
speed and 2019's auto fatality rate.
1:57
Although it's possible examining trends
over time might tell a different story.
2:03
For my third sketch,
2:09
I wondered whether auto travel was
getting safer in America in general.
2:10
We can't tell by looking at
2019 statistics, but IIHS
2:15
provides a page called yearly snapshots
with annual statistics since 1975.
2:20
I've drawn this out as a line chart,
2:27
focusing only on deaths
per 100,000 people.
2:30
And it looks like driving was
considerably more dangerous in
2:33
America in the late 1970s
and early 1980s,
2:38
with another steep decline
between 2005 and 2010.
2:42
This yearly snapshot also gives
us an indication of the role
2:47
driver speed plays in fatal accidents.
2:51
I've drawn this is a pie chart, and
2:55
we can quickly see that over half
the road deaths in America in 2019
2:57
involved cars traveling 55
miles per hour or faster.
3:03
While it makes sense that faster speeds
would lead to worse accidents, I'm not
3:07
sure this chart is sufficiently meaningful
for either of my personas to share.
3:12
After doing a bit more research,
I gave another scatterplot a try.
3:17
This time comparing the amount of time
spent driving 70 miles per hour or
3:22
greater in each state versus
the fatality rate per 100,000 people.
3:27
This time the correlation is stronger
than in my previous sketch, and
3:33
I'm inclined to believe the data I'm
using is more meaningful since it
3:37
measures actual time spent driving fast.
3:41
Wyoming catches my eye here since
it's the state with both the fastest
3:44
drivers and the highest
auto fatality rate.
3:49
However, I may have the opposite
problem from my previous sketch.
3:52
While my pie chart was probably
too broad to interest my personas,
3:56
this one might be too complex.
4:01
So then I wondered, is it possible to
combine the choropleth map of auto
4:03
fatality rates with average driver speeds?
4:08
Our previous data set listing the amount
of time spent driving 70 miles per hour or
4:11
faster seemed difficult
to visualize on a map.
4:17
So I tried instead working with a
2016 set of average top speeds.
4:21
While these numbers should be easy for
American drivers to read—
4:27
78 miles per hour on Texas roads,
62 miles per hour in Oregon—
4:32
once I sketched it out, the correlation
between average driver's speeds and
4:37
the 2019 auto fatality
rate looked somewhat weak.
4:43
In the end, I decided based on the data
available to return to my first sketch.
4:47
Limiting my data to the death
rate per 100,000 people
4:53
told the most straightforward
story and the map of America
4:57
should be recognizable to
drivers in my audience.
5:02
I also feel good about
IIHS as a data source.
5:05
The 2016 list of average top highway
speeds is both an older data set and
5:09
not a firsthand source, so
I feel less confident about using it.
5:15
All right, now I'm ready to
build my choropleth map, but
5:21
what tool should I
use to begin my design?
5:25
In the next video,
we'll take a brief look
5:28
at different tools available
to create our visualization.
5:31
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