Data Analysis Week VII: Uncertainty and Error

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Questions and Answers

What is a disadvantage of using unclassed maps?

They can be hard to read. (correct)

They allow for quick decision-making.

They can be easier to interpret.

They provide detailed classifications.

Which of the following types of maps is primarily used for representing line data?

Flow map (correct)

Choropleth map

Isoline map

Density Dot map

Which of the following is NOT a type of central tendency in aspatial descriptive statistics?

Mean

Mode

Variance (correct)

Median

What do Theissen polygons (Voronoi polygons) help to determine?

The closest point from a set of points to any location within the polygon Signup and view all the answers

Which index is used to measure the spatial autocorrelation of nearby values?

Moran's index Signup and view all the answers

What is the primary difference between uncertainty and error in data analysis?

Uncertainty assesses the understanding of data representation, whereas error quantifies measurement discrepancies. Signup and view all the answers

Which type of uncertainty relates to the challenges of conceptions of place?

Conceptual Uncertainty Signup and view all the answers

What is the main purpose of internal validation in data modeling?

To evaluate the model against a separate test dataset for accuracy. Signup and view all the answers

What does the ecological fallacy refer to in statistical analysis?

Drawn conclusions about individuals from aggregate statistics, leading to inaccuracies. Signup and view all the answers

In spatial selection operations, what does the topological attribute 'contains' signify?

A region completely encloses another region within its boundaries. Signup and view all the answers

What does a high Z score indicate in Hot Spot Analysis?

Spatial clustering of high values Signup and view all the answers

Which of the following is a local function in Raster Analysis?

Mathematical operations applied to each cell Signup and view all the answers

In the context of cost surfaces, what does 'friction' typically refer to?

The cost associated with terrain traversal Signup and view all the answers

What is the first step in the Watershed Delineation process?

Condition DEM Signup and view all the answers

How is slope commonly expressed in terms of percentage?

Rise divided by run multiplied by 100 Signup and view all the answers

What is the output of logical operations in raster analysis?

Binary values indicating presence or absence Signup and view all the answers

What distinguishes passive sensors from active sensors?

Active sensors measure the return of emitted signals. Signup and view all the answers

What is the primary purpose of viewshed analysis?

To determine visible areas from a specific viewpoint Signup and view all the answers

What is the primary purpose of using a variogram model in spatial analysis?

To interpolate the entire surface Signup and view all the answers

Which statement best describes the differences between prediction and prescription in spatial modeling?

Prediction determines what will happen over time, while prescription evaluates hypothetical scenarios. Signup and view all the answers

Which type of error is characterized by random fluctuations in data without identifiable sources?

Random error Signup and view all the answers

What is NOT a type of spatial data accuracy measure?

Reliability accuracy Signup and view all the answers

Which of the following best defines 'cartographic models' in spatial modeling?

Simplified representations illustrating spatial relationships and processes Signup and view all the answers

Which of the following standards is primarily assessed for data quality in spatial data?

Spatial data accuracy standards Signup and view all the answers

What does 'lineage' refer to in the context of documenting spatial data accuracy?

Sources, methods, and timing involved in data creation Signup and view all the answers

Which approach is NOT considered a method for inputting data in spatial analysis?

Time-series analysis Signup and view all the answers

What does the nearest neighbor index value of 0.5 indicate about spatial distribution?

The distribution is clustered. Signup and view all the answers

What is the purpose of using a diverging color ramp in data visualization?

To emphasize differences around a meaningful zero point. Signup and view all the answers

What type of vector overlay operation would retain all areas from both input layers?

Union Signup and view all the answers

Which sampling method is characterized by the least inherent bias?

Random sampling Signup and view all the answers

Which type of raster function considers the value of individual cells only?

Local Signup and view all the answers

What does plan curvature measure in a topographic context?

Concavity or convexity in the contour direction. Signup and view all the answers

What type of map illustrates information visible or not visible from a specific viewpoint?

Viewshed map Signup and view all the answers

What type of region cannot be analyzed using map algebra?

Points Signup and view all the answers

Which map type is most suitable for representing population density?

Choropleth map Signup and view all the answers

What does Moran’s Index measure?

Spatial autocorrelation Signup and view all the answers

What is the purpose of watershed delineation?

Define flow accumulation and stream outlets Signup and view all the answers

How is slope commonly calculated?

Angle derived from rise over run Signup and view all the answers

Which sampling method is designed to reduce travel time?

Cluster Signup and view all the answers

In Kriging, what is a variogram used for?

Modeling spatial trends Signup and view all the answers

Which type of error in GIS data is described as persistent or identifiable bias?

Systematic Signup and view all the answers

What is the key difference between accuracy and precision?

Accuracy reflects how close measurements are to true values, precision reflects consistency Signup and view all the answers

Study Notes

Week VII

Uncertainty vs. Error: Uncertainty is a measure of understanding the difference between dataset content and real phenomena. Error is the measurement of uncertainty.
Types of Uncertainty:
- Conceptual Uncertainty: Place conceptions are problematic, questioning the best unit for analysis.
- Representational Uncertainty: Choosing between continuous field or discrete object views for analysis.
- Analytical Uncertainty: Internal and external validation, plus error propagation and the modifiable area unit problem (MAUP). Ecological fallacy, is a type of error in interpreting statistical data about aggregated groups.
Internal & External Validation:
- Internal: Split data into training and test sets. Train model on training set. Test model on test set to check accuracy.
- External: Use all data to train. Validate the model using independent datasets. High accuracy in external validation shows a robust model.
Error Propagation: Errors during interpretation of statistical data.
Ecological Fallacy: Interpreting characteristics of individuals based on aggregate statistics can lead to false conclusions about social phenomena. Aggregation reduces information.
Scope:
- Local: Point to point measurement
- Neighborhood: Adjacent regions have input
- Global: Entire input data layer may influence output
Methods of Selection:
- Set algebra: <, >, =, <>,...
- Boolean Algebra: AND, OR, NOT
- Spatial Operations: Topology, Attributes (e.g., size, directionality).
- Spatial selection operations:
 - Topological: (e.g., in, adjacent, contains)
 - Spatial attributes: (e.g., state size, directionality)
 - Attributes of regions: (e.g., state population)
Classed vs. Unclassed:
- Classed: Pros: more control over map; Cons: need to make choices.
- Unclassed: Pros: no decisions to make; Cons: might be hard to read.

Week VIII

Choosing Map Types: Point, line, and polygon data types are used.
Differing Map Types: Dot map, density dot, picture symbol, graduated symbol, flow map, area qualitative, stepped surface, choropleth, hypsometric map, dasymetric map, cartogram, isoline map, image map, and multivariate map.
Differing Views of Maps: Fishnet/gridded, realistic, hillshade relief are views of different maps.
Aspatial Descriptive Statistics: Range (minimum, maximum), central tendency (mean, median, mode), variation (variance, standard deviation) are described.
Theissen (Voronoi) Polygons: A technique to partition space based on distance to points. Each polygon contains locations closer to one point than any other.
IDW vs. Spline: Methods of interpolation

Week IX

Cluster analysis: Moran's index and nearest neighbor index are statistical tools for spatial autocorrelation.
Raster analysis: Local and global functions, reclassification.
Cost surfaces: Calculate cost/distance
Digital Terrain Models (DTMs): Relating digital surface models (DSMs) to DTMs. Calculating slope.
Viewshed: Area visible from a point.
Hydrologic functions: Area contributing flow to a point.

Week X

Drainage Networks: Watershed delineation process. Condition DEM, Flow direction, Flow accumulation, Stream definition, Outlet identification, and Watershed delineation. Sample methods.
Sampling Methods: Systematic, random, cluster, adaptive. Discuss advantages and disadvantages of each.
Spatial Estimation: Raster surface, boundaries, cell dimensions, interpolation method, contour lines, and Thiessen polygons.

Week XI

Trend Surface Interpolation: Fitting a trend surface through measured points.
Kriging: Using a statistical model to estimate spatial variables.
Lag Distance & Variograms: Distance between points used in analysis. Plots of semivariance over lag distances.
Spatial modeling: Solving problems. Describing spatial patterns or processes, associations, and factors affecting distribution.
Prediction and Prescription: Difference between predicting what will happen and prescribing actions.
Types of spatial models: Simple spatial, spatio-temporal, and cartographic models.

Week XII

Data Standards: Used to format, asses, document, and deliver data.
Spatial Data Standards: Media standards (physical specifics), spatial data accuracy (data quality), documentations.

General Notes (across multiple weeks)

Accuracy vs Precision: Difference between the correctness and consistency of a measurement.
Data Accuracy: Error. Difference between encoded and actual value, including random, systematic, gross errors.
Documentation of spatial data accuracy: Positional (how points in data relate to reality), attribute (accuracy of attributes), logical (inconsistency of attributes), and completeness (covering all areas).
Expressing Accuracy: How close a measurement is to the truth. Quantify as a number or probability distribution.
GIS Certifications and Technical Knowledge: Different certifications and requirements.

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Description

This quiz explores the concepts of uncertainty and error in data analysis. It covers types of uncertainty, internal and external validation, and provides insights into analytical methods and error interpretation. Test your understanding of these critical topics in data science.