Organic Farming Proposal
Organic Farming Proposal
Michael Lewis
Part I
Measurement Types
There are 4 major measurement types used in statistical
data. First, Nominal data is a set of data that can be categorized into set groups.
An example of this would be election results falling into categories of
republican, democrat, or independent. Figure 1 is the electoral map from the
2000 presidential election. Each state falls into a category of red for republican
and blue for democrat in a true nominal way. This style and example are popular
in the media today for its level of simplicity and how it doesn’t require much
to understand what is being displayed.
Secondly, Ordinal data is data that is ordered into some
sort of rank based on any number of qualities. This could be data as a part of
the world’s happiest countries. Figure 2 displays how data can be ordered with
a ranking. This particular example of the happiest countries visualized where
the happier countries are and based on the colors also gives the reader a
general sense of where the happiest regions are too.
Figure 2: Happiest Countries
Next, Interval data is data that is segmented in equal
sections. Each section contains the same amount of units in between. It is
important, however, to point out that when using interval data, that zero is
simply a measurement, not a starting point. An example of interval data may be
percentage population change, it could increase or decrease. Figure 3 is
population change by county between 2014 & 2015 and is a great example of
the intervals used to display positive and negative change. It also shows how
the value of 0 is merely an indication rather than an origin.
Figure 3: Population Change 2014-15
Lastly, Ratio is data that is taken against the greater set
of data to show a contrast between the two. This could be shown in comparing
single men against single women across the country. Figure 4 shows just that.
The key part of the map is the use of ratios to show the difference between men
and women. Based on the size and color of the circle, you can clearly see which
group is larger in that particular area.
Part II
Map Proposal to Clients
First
and foremost, the push for organic food is growing with a movement capturing
the nation in search for healthier foods in a time where processed food rule
supreme. As science continues to expose the health risks related to food that
is processed or has more chemical additives and preservatives, many people are
taking initiative and spending the extra money for organics. That being said,
in the state of Wisconsin, the number of USDA Certified Organic Farms are on
the rise and it is still a young market. To help show how Wisconsin’s organic
farms are disbursed, I’ve prepared the data in 3 separate ways. By presenting
the data as equal intervals based on range, using a quantile method, and
Natural breaks we see how the organic farms cluster in certain parts of the
state. Figure 5 is the Equal Intervals map. Figure 6 is the Quantile map.
Figure 7 is the Natural Breaks map.
Figure 5: Equal Interval Map of Organic Farms
Figure 6: Quantile Map of Organic Farms
Figure 7: Natural Breaks Map of Organic Farms
I would use figure 6 as the map to present to
the clients. Using a Quantile method prevents them from assuming that all of
the counties in the lowest category have zero organic farms. It gives the
counties with lower amounts of farms a better distinction amongst themselves
and allows for an easier interpretation of those data points, especially as
most of the points fall in those categories. Additionally, as any map maker
knows, there is flexibility in the truth with a map. Yes the range between 21
and 223 is near ridiculous, but this map shows where the top counties of
organic farms are and it draws your eyes to a clear trend that the western part
of Wisconsin grows more organics than the east, showing future clients the
market saturation and potential for investment. If the client is looking to
increase organic farms in a given county, it is important to see where the opportunities
are and this map displays that the best.
Sources:
Figure 1:
“2000 Presidential Election.” Presidential Election of 2000, 270 To Win, www.270towin.com/2000_Election/.
Figure 2:
“Happiest Countries in the World.” Maps of World, www.mapsofworld.com/world-maps/happiness.html.
Figure 3:
Kiersz, Andy. “These Are the Fastest Growing and Shrinking Counties in America.” Business Insider, Business Insider, 24 Mar. 2016, www.businessinsider.com/county-population-change-map-2016-3.
Figure 4:
Soma, Johnathan. “The New, Interactive Singles Map.” The New, Interactive Singles Map., jonathansoma.com/singles/.
Data provided by:
United States Census Bureau 2012 Agricultural Data
Sources:
Figure 1:
“2000 Presidential Election.” Presidential Election of 2000, 270 To Win, www.270towin.com/2000_Election/.
Figure 2:
“Happiest Countries in the World.” Maps of World, www.mapsofworld.com/world-maps/happiness.html.
Figure 3:
Kiersz, Andy. “These Are the Fastest Growing and Shrinking Counties in America.” Business Insider, Business Insider, 24 Mar. 2016, www.businessinsider.com/county-population-change-map-2016-3.
Figure 4:
Soma, Johnathan. “The New, Interactive Singles Map.” The New, Interactive Singles Map., jonathansoma.com/singles/.
Data provided by:
United States Census Bureau 2012 Agricultural Data
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