Covers computational and data analysis techniques for environmental engineering applications. First third of subject introduces MATLAB and numerical modeling. Second third emphasizes probabilistic concepts used in data analysis. Final third provides experience with statistical methods for analyzing field and laboratory data. Numerical techniques such as Monte Carlo simulation are used to illustrate the effects of variability and sampling. Concepts are illustrated with environmental examples and data sets. This subject is a computer-oriented introduction to probability and data analysis. It is designed to give students the knowledge and practical experience they need to interpret lab and field data. Basic probability concepts are introduced at the outset because they provide a systematic way to describe uncertainty. They form the basis for the analysis of quantitative data in science and engineering. The MATLABĺ¨ programming language is used to perform virtual experiments and to analyze real-world data sets, many downloaded from the web. Programming applications include display and assessment of data sets, investigation of hypotheses, and identification of possible casual relationships between variables. This is the first semester that two courses, Computing and Data Analysis for Environmental Applications (1.017) and Uncertainty in Engineering (1.010), are being jointly offered and taught as a single course.

In this math activity, learners prepare jumping jack data to send to officials on the planet Jumpalot. Learners record how many jumping jacks they can do in ten seconds and use their knowledge of time conversions to figure out how many jumping jacks they could complete in a minute all the way to a year. Learners then organize group data and explore mean, median, and mode and the effects extreme values have on these measures. Finally, learners brainstorm the advantages and disadvantages each measure offers. This lesson guide includes questions for learners, assessment options, extensions, and reflection questions.

These data provide a historical view of the ice cover on 3 Wisconsin lakes that either are in close geographically close proximity to many students or are located close to the Capital of WI -- thereby providing relevance to Wisconsin students. These data can provide an anchoring phenomena for approaching concepts of phase changes, thermal energy transfer and global climate change. These data were extracted from: Wisconsin State Climatology OfficeNelson Institute for Environmental Studieshttps://climatology.nelson.wisc.edu/first-order-station-climate-data/madison-climate/lake-ice/madison-lake-ice-summ

These are source data and an article from the Journal "Nature" to use with students for anchoring the effects of Global Climate change on ice durations of local lakes. The article describes ice conditions and methadologies of 6 Wisconsin Lakes. There are links to raw data that can be used to generate graphs and develop sensemaking for students.