1. Quantitative vs. Qualitative Data
Displaying Data
Quantitative vs. Qualitative Data

2. Symbolizing Features: Qualitative

3. Symbolizing Features: Quantitative

4. Qualitative Symbology
Different features get different symbols or colors, it is not dependent on a quantitative value. Limit to 10 unique values generally.
Same symbol
Unique symbol (value)

5. Quantitative Symbology
Uses values, or quantities, contained in numeric attribute fields
Graduated colors:
The color varies with the
numeric attribute value,
Usually the dark the color
The higher the value.
Up to 5 or 6 shades of one color maximum.

6. Quantitative Symbology
Graduate Symbols
The symbol size varies with
the attribute value.
Usually the larger the symbol
the greater the value.
This shows relative values,
not absolute values.

7. Quantitative Symbology
Proportional symbols
Symbols vary in size
to show exact values.

8. Normalizing Data
Quantitative symbology can be normalized based upon the attributes of another field.
For example population normalized by area
Sales per state normalized by population.

9. Normalizing data

10. Displaying multiple attributes
Symbolize features based on more than one attribute.
Street type and traffic volume.
Parcel land use and value.

11. Quantitative Symbology
Dot Density
Good for showing
areas of low and
high concentrations

12. Classifying the data based upon attribute value
Default

13. Classification places attribute values into groups
Natural breaks (default) – the gaps in the data are identified and the intervals are assigned accordingly. Shows clusters or concentrations of values.
Equal interval – range of values is equal within each class (61-70, 71-80, 81-90, etc.) Bands of temperature.
Quantile – the number of features with in each class are the same (top 25%)

14. Classifying the data based upon attribute value
Standard Deviation- the range of values with each class is based on the standard deviation of the data. Shows the amount the attribute value varies from the mean. (crops which area perform better than average, which perform worse than average)
Manual – defined by the user.

15. Histograms