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water science
I. WATERSHED AND AQUATIC
    SCIENCE FUNDAMENTALS
1: Watershed science
and society
2/3: Lake ecology
4/5: Stream ecology
II. EXPERIMENTAL
    DESIGN
6: Problem and objective formulation
III. DATA COLLECTION
7: Watershed / land use surveys
8/9: Lake surveys
10/11: Stream surveys
12: Remote sensing and Internet data sources
IV. DATA MANAGEMENT
13: Quality assurance and quality control
14: Data types, sources,
and retrieval
15: Spreadsheets and nonspatial databases
16: GIS spatial databases
V. DATA ANALYSIS, INTERPRETATION,
        AND PRESENTATION
17: Elementary statistics
18: Applications of
regression to water
quality analysis
19: GIS / spatial analysis
20: Data visualization and presentation
21: Introduction to modeling
VI. MANAGEMENT POLICY
        AND OUTREACH
22: Regulations and compliance monitoring
23: Watershed management
24: Lake restoration
25: Stream restoration
26: Community education
and involvement
27: Educating decision-makers
 
 
  Unit V Data Analysis, Interpretation, and Presentation


MODULE 17 ELEMENTARY STATISTICS

• Significant figures
• Measures of variation (e.g., mean, median, mode, skew, standard deviation, RPD, CV)
• Interpolation, extrapolation
• Hypothesis testing
• Principles of exploratory data analysis (EDA)

- Traditional EDA techniques
- Emerging EDA techniques
- Survey of EDA software

MODULE 18 APPLICATIONS OF REGRESSION TO WATER QUALITY ANALYSIS

• Basic concepts and applications
• Basic linear regression
• Detecting and analyzing trends
• Curve fitting with Excel
• Assumptions and limitations of regression analysis
• Regression software survey

MODULE 19 GIS/SPATIAL ANALYSIS

• Vector analyses (e.g., unions, intersections, clipping, buffer analyses)
• Raster analyses (e.g., neighborhood statistics, interpolation, filtering)
• Patch statistics (e.g., survey, assumptions and use)

MODULE 20 DATA VISUALIZATION AND PRESENTATION

• Basic graphical techniques and software
• Data visualization techniques

MODULE 21 INTRODUCTION TO MODELING

• Underlying assumptions of models
• Limitations of models
• Types of models (e.g., conceptual, empirical, mechanistic)
• Applications of models

- Pollutant loads (e.g., TMDLs)
- Lake water quality (e.g., WILMS and other spreadsheet models)
- Streams (e.g., In-stream Flow Incremental Methodology – IFIM)
- Stormwater, urban runoff


  


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date last updated: Monday March 29 2004