Qualitative and Quantitative Information

Qualitative and Quantitative Information PowerPoint PPT Presentation


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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

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