Examination and Study Questions for Error, Accuracy, and Precision

  1. Essay Questions
  2. Short Answer
  3. Multiple-choice

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1. Essay Questions

Limit each essay to two double-spaced typewritten pages plus references.

  1. How can sensitivity analysis be used to judge the level of precision and accuracy required to meet the needs of a GIS application?

  2. Is it fair to say that an undocumented dataset is a worthless dataset? What documentation makes a dataset valuable?

  3. Why must standards for data accuracy address both procedures and products?

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2. Short Answer

Limit your answers to no more than 100 words.

  1. What are three sources of error in a GIS database?

    1. Obvious error
    2. Errors arising from natural variation or original measurement
    3. Processing error

  2. What is the difference between precision and accuracy?

    • Accuracy is how well information or data matches true values. Precision refers to the level of measurement

  3. What is "false precision"? How can the results of GIS analysis be reported to avoid this pitfall?

    • False precision is reporting GIS analysis or finding to a level of precision or accuracy impossible to achieve from the source materials. GIS solutions are best reported as ranges or rankings, or presented within statistical confidence intervals.

  4. Why are mistakes caused by "false scale" so common when using automated mapping systems?

    • Due to the ease in which one may change scale, i.e. "zoom in and zoom out", but the automated map is only as accurate as the source scale.

  5. How are accuracy and precision related to the scale of USGS map products?

    • USGS employs accuracy standards that require "horizontal accuracy as 90 per cent of all measurable points must be within 1/30th of an inch for maps at a scale of 1:20,000 or larger, and 1/20th of an inch for maps at scales smaller that 1/20,000." Different scale maps have different levels of accuracy, e.g. a 1:1,200 map is accurate to (3.33 ft, whereas a 1:24,000 is accurate to (40.00 feet.

  6. What is meant by a "pedigree" for data and why is it important to understanding the quality of spatial databases?

    • Data should be documented as to accuracy and precision in reports that tell you exactly how the maps and datasets were compiled. Unreliable, unknown, or poor quality data will produce uncertain or spurious GIS solutions.

  7. What is the difference between "propagation of error" and "cascading of error"?

    • Propagation occurs when one error leads to another. Propagation is often additive in nature, as when maps of different accuracy are collated. Cascading of error occurs when erroneous, imprecise, or inaccurate information is combined selectively into new layers and coverages, that is errors are allowed to propagate unchecked from layer to layer.

  8. According to P.A. Burrough (1986) in Chapter 6 Principles of Geographic Information Systems for Land Resources Assessment, what are four types of error arising from natural variation or original measurements that affect the quality of GIS datasets?

    1. Positional accuracy
    2. Accuracy of content
    3. Measurement error
    4. Natural variation in data collected

  9. List two sources of error that may be "hidden" from the GIS user, that is error resulting from natural variation, original measurement, or processing.

    1. Numerical errors
    2. Uncalibrated measuring equipment
    3. Errors in topological analysis
    4. Classification and generalization errors
    5. Original observations are faulty
    6. Digitizing and geocoding errors

  10. What is the difference between positional accuracy, conceptual accuracy, and attribute accuracy?

    • Positional accuracy is dependent on the accuracy standards of a map, that is what is the probable location defined by some parameter such as (10 feet. Conceptual accuracy is based on how one classifies information into appropriate categories. Attribute accuracy is the level of non-spatial data accuracy linked to location. It may also include the level of detail assigned to a location.

  11. List at least five problems that arise when "paper" maps are converted to "digital" maps.

    1. digitizing errors
    2. geocoding errors
    3. Physiological errors of operator
    4. Damaged source maps
    5. Rasterizing a vector map
    6. Propagation errors
    7. Numerical processing errors

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3. Multiple-choice questions

Choose the best or most appropriate answer(s) to the question.

  1. When an error in a dataset leads to the commission of another error this is called:

    1. false precision
    2. propagation
    3. spawning
    4. horizontal error
    5. cascading
    6. breeding

  2. Which of the following statements about accuracy and precision are true:

    1. Conceptual accuracy means employing the correct database model to represent a real-world feature or event
    2. False precision applies only to positional accuracy
    3. Measures of attribute accuracy vary depending upon the level of measurement of the attribute
    4. Cohen's Kappa is one measure of positional accuracy

  3. Which of the following statements is true?

    1. a precise measurement may be inaccurate
    2. an accurate measurement may be imprecise
    3. accuracy applies only to attribute data whereas precision applies to both attribute and geographic data
    4. high accuracy and high precision are both expensive to acquire

  4. The degree to which information on a map or in a digital database matches true or accepted values is referred to as:

    1. precision and accuracy
    2. precision
    3. accuracy
    4. data quality
    5. attribute information
    6. None of the above

  5. The term "precision" refers to:

    1. highly accurate data
    2. measurements that are within (1mm
    3. logical accuracy
    4. the level of measurement and exactness of description in a GIS database
    5. All of the above

  6. Examples of non-obvious sources of data are:

    1. areal cover
    2. map scale
    3. numerical errors
    4. format
    5. density of observations

  7. Propagation occurs when:

    1. different scale maps are digitized
    2. data quality reports are missing
    3. one error leads to another
    4. data cascades
    5. none of the above

  8. GIS solutions are best reported:

    1. using calibration sensitive analysis
    2. as ranges or rankings
    3. with surrogate data analysis
    4. with statistical confidence intervals
    5. all of the above
    6. 2 and 4 only

  9. Modern GIS and CAD packages allow easy changes to map scales. Enlarging a small scale map:

    1. provides higher levels of observation
    2. increases the density of observations
    3. does not increase its accuracy or level of detail
    4. allows better use of surrogate data

  10. Many agencies now provide data quality reports for GIS data. A data quality report:

    1. ensures GIS solutions will be correct
    2. requires sensitivity calibration
    3. ensures precision and accuracy in digital data
    4. provides information on how maps and data sets were compiled
    5. none of the above
    6. 2 and 4

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Created on 22 Dec 95. Revised on 5 February 2000. LNC