CHOROPLETH MAPS

1
CHOROPLETH MAPS

• INTRODUCTION
• DATA STANDARDIZATION
• DATA CLASSIFICATION
• DATA SHAPE
• METHODS OF DATA CLASSIFICATION

2
ChoroplethMaps
3
Intro to Choropleth Maps

• Two major limitations of choropleth maps
• They do not portray the variation that may
  actually occur within the enumeration units.
• The boundaries of the enumeration unit are
  arbitrary and are thus unlikely to be associated
  with the major discontinuities in the actual
  phenomenon.

4
DATA STANDARDIZATION

• Proportion

5
DATA STANDARDIZATION

• Ratio of area based counts

6
DATA STANDARDIZATION

• Density

7
DATA STANDARDIZATION

• Ratio of 2 count variables, neither of which
  involves area
• For example, we want to find out the rate of
  cancer deaths in the United States.
•  
• Cancer deaths for a county/population for the
  county number of cancer deaths/100,000 people
•  
• When we solve for the number of cancer deaths, we
  rewrite the equation to the following
•  
• Number of cancer deaths (Cancer deaths for a
  county/population for the county) 100,000
•  
• The resulting number of cancer deaths is actually
  the cancer death rate per 100,000 people.

8
DATA CLASSIFICATION

• Simplifying data into classes
• The map-reader is generally not going to be able
  to discriminate between more than 5 to 7 classes.
• All systems of classification depend upon the use
  of "exhaustive" and "mutually exclusive"
  categories.

9
Explore the Dataand Its Shape
10
Common Methods of Data Classification

• Equal Intervals
• The equal intervals are determined by
•  (Highest observation lowest observation) /
  number of class
• 15 5/5 2
•  5 7
• 7.1 9
• 9.1 11
• 11.1 13
• 13.1 15

11
Common Methods of Data Classification

• Quantiles
• Data are ranked in order and an equal number of
  observations are placed in each class.
• Different names are given to the different number
  of classes
• 4 classes quartiles
• 5 classes quintiles

12
Common Methods of Data Classification

• Mean and Standard Deviation
• The data must be normally distributed.
• Calculate the mean of the data and the standard
  deviation for the data
• Develop classes from the mean 1 sd and the mean
  2 sd

13
Common Methods of Data Classification
14
Common Methods of Data Classification

• Natural Breaks
• Considering the natural grouping of the data.
• Graph the data using a dispersion graph, a
  histogram, a scatter plot, or a simple line
  graph.
• Look for natural breaks or clusters in the data.