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Qualitative and Quantitative Information

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**1. **Qualitative and Quantitative Information

**3. **Level of Measurement The level of measurement refers to the relationship among the values that are assigned to the attributes for a variable.
Nominal (The word "nominal" means "in name.")
Level of data measurement that is non comparative, usually representing a description or name
Ordinal (The word "ordinal" means "in order.")
Ranked data (e.g., good, better, best) that are comparable only within a given spectrum.
Interval
Ratio

**4. **Nominal Level The least precise level of measurement is the nominal level.
Example of nominal-level variables are
Sex (with the categories of male and female),
ethnicity (categories could include African American, Latino, and white),
Political Party Identification (Democrat, Republican, Independent, etc.) and
Religion (Catholic, Protestant, Jewish, Hindu, Buddhist, etc.).

**5. **Ordinal Level If we had a variable whose categories did have an order, we might have an ordinal-level variable
Example is "social class," with categories such as lower class, working class, middle class, and upper class.

**6. **Interval Level Interval scales are numerical scales in which intervals have the same interpretation throughout.
As an example, consider the Fahrenheit scale of temperature. The difference between 30 degrees and 40 degrees represents the same temperature difference as the difference between 80 degrees and 90 degrees. This is because each 10 degree interval has the same physical meaning.

**7. **Ratio Level The highest level of measurement is the ratio level.
Variables measured at the ratio level have all the characteristics of nominal-, ordinal-, and interval-level measures

**9. **Types of Cartographic Symbols Point symbols
Line symbols
Area symbols

**10. **Characteristics of Cartographic Symbols Shape
Size
Hue
Tonal value
Texture
Orientation

**11. **Types of Cartographic Symbols

**12. **Point Symbols Point data can be symbolized at a point or aggregated at a point
Point symbols are quantitative or qualitative
Nominal point symbols maps
Ordinal point symbols maps
Proportional point symbols maps

**13. **Nominal Point Symbols

**14. **Ordinal Point Symbols Maps:

**15. **Graduated Point Symbols : True proportional symbols maps
Range-graded symbols
Other graduated symbols maps

**16. **True Proportional Symbols Maps: The data is ranked on a measured scale.
The size of each symbol is proportional to the value of the feature on the scale.
Interval/Ratio data types :

**17. **True Proportional Symbols Maps:

**18. **Range-graded Symbols: The data is ranked on a measured scale.
The data is divided into ranges:
Quartile, natural breaks and user defined
Symbol size is based on the range in which the value falls
Quantiles> It is approach
Quintile > If data divided in 5 equal parts
Quartile > If data divided in 4 equal parts
Decile > If data divided in 10 equal parts

**19. **Range-graded Symbols:

**20. **Range-graded Symbols:

**21. **Other Point Maps

**22. **Dot-distribution map

**23. **Dot-distribution map

**25. **Dot Maps:

**26. **Dot Maps:

**27. **Dot Maps:

**28. **Dot-distribution map

**29. **Symbolizing Data with Lines:

**30. **Symbolizing Data with Lines:

**31. **Symbolizing Data with Lines:

**32. **Choropleth Maps Classless choropleth map
one color/shading pattern per attribute value
impractical as it is difficult to interpret
Classed choropleth
easier to interpret with fewer color/shading patterns, usually 5-20 different classes
3 steps
1. attribute data classification
2. color / shade pattern assignment
3. custom design

**33. **1. Attribute data classification converting interval/ratio data into ordinal data)
to group attribute values into a distinct number of ranked classes, usually 5-20 classes
data classification methods
equal interval
equal frequency or even grouping (Quintiles)
natural break or user specified
different methods are selected to convey a different message or distributional pattern
An example is provided on the next page to show results of different data classification methods
with 19 observations
assuming 5 ordinal classes
by means of graphing sorted data

**36. **Isolines Device for showing spatial distribution.
Refers to any line that joins points of equal value.
Common types of isolines
Contour line (Equal Elevation)
Isobar (A line of equal or constant pressure)
Isotherm (A line of equal or constant temperature)
Isohyet (A line of equal amounts of precipitation)
http://www.theweatherprediction.com/basic/isopleths/

**37. **Drawing Isolines

**38. **Use of Isolines (Isohyet)

**39. **Basic Characteristics of Isolines Closed lines, having no end.
Represent gradations in quantities.
Maintain a constant interval between them.
Closeness depends on gradient (slope).

**40. **Type of Isolines Isometric lines
Based on control points
Isopleths
Based on areal averages

**41. **Isometric Maps

**42. **Isometric Maps - Isolines

**43. **Isopleth Maps Areal statistics shown

**44. **Prism Maps

**45. **Choropleth Maps tonal shadings are graduated to represent areal variations in number or density within a region, usually a formal region.

**46. **Choropleth Maps tonal shadings are graduated to represent areal variations in number or density within a region, usually a formal region.

**47. **Choropleth Maps tonal shadings are graduated to represent areal variations in number or density within a region, usually a formal region.

**48. **Categorizing Data for Choropleth Maps

**49. **Categorizing Data for Choropleth Maps

**50. **Isopleth Maps isolines connect points of equal magnitude.

**51. **Isopleth Maps isolines connect points of equal magnitude.

**52. **Dot density maps dot frequency displays quantity

**53. **Proportional circle map size of circle varies with attribute data

**54. **Cartogram – a map presentation of statistical data, often more than one attribute displayed for each area, often as miniature bar graphs or other graphics

**55. **Cartogram – a map presentation of statistical data, often more than one attribute displayed for each area, often as miniature bar graphs or other graphics

**56. **Cartogram

**57. **Cartogram