# Data Analysis For Water Resources

 DESCRIPTION This course covers analysis and interpretation of water resources engineering data. Empirical, analytic, and statistical decomposition of spatial and temporal data are explained from a user’s, not mathematician’s perspective. Hands-on analysis of example data sets make the methods come alive. LEARNING OBJECTIVES: Participants will: Learn how to determine the best approach(es) for analyzing and interpreting typical water data. Experience applying standard and non-standard analyses and tools to data sets. Understand how to extract meaning from noisy, error-filled, or multiple-forcing data. Learn methods for communicating data by graphical displays. INTENDED AUDIENCE The course will be useful to engineers, scientists, and technicians who work with water resources data and need to extract meaningful information from those data. A basic knowledge of engineering mathematics is needed. (A refresher module is available for those that need it.) COURSE BENEFITS Be able to answer common questions about data: Which data points are likely to be errors? Is there a statistically significant trend or change? Can a causal relationship between two parameters be established? Can the noise be reduced or eliminated? Learn how to present data so that non-specialists understand. Earn PDH.   SUMMARY OUTLINE Introduction – types and applications of data analysis Data Characteristics – time series and spatially distributed, signal vs. noise, error and mistakes, uniform interval vs. non-uniform, gaps, deterministic vs. stochastic, fractals, Software introductions, EXCEL, MATLAB, others Statistics review – random variables, distributions, statistical measures Standard Analyses – Data pre-conditioning, scatter diagrams, RMS errors, linear and non-linear regression, coefficients of correlation, filtering Empirical relationships – Buckingham Pi theorem, cluster maps, multiple correlation coefficients and tests of distribution Advanced topics: Harmonic and Spectral analyses   LENGTH: 32 hours