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Air Quality Data Mining: Mining the US EPA AirData website for student-led evaluation of air quality issuesLearning ObjectivesStudents will be able to:
- Describe various parameters of air quality that can negatively impact human health, list priority air pollutants, and interpret the EPA Air Quality Index as it relates to human health.
- Identify an air quality problem that varies on spatial and/or temporal scales that can be addressed using publicly available U.S. EPA air data.
- Collect appropriate U.S. EPA Airdata information needed to answer that/those questions, using the U.S. EPA Airdata website data mining tools.
- Analyze the data as needed to address or answer their question(s).
- Interpret data and draw conclusions regarding air quality levels and/or impacts on human and public health.
- Communicate results in the form of a scientific paper.
Teaching RNAseq at Undergraduate Institutions: A tutorial and R package from the Genome Consortium for Active TeachingLearning Objectives
- From raw RNAseq data, run a basic analysis culminating in a list of differentially expressed genes.
- Explain and evaluate statistical tests in RNAseq data. Specifically, given the output of a particular test, students should be able to interpret and explain the result.
- Use the Linux command line to complete specified objectives in an RNAseq workflow.
- Generate meaningful visualizations of results from new data in R.
- (In addition, each chapter of this lesson plan contains more specific learning objectives, such as “Students will demonstrate their ability to map reads to a reference.”)