A smoggy harbor in Shanghai

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ENVS 491-001 – Environmental Applications of Statistics
3 Credits, Summer 2019
MTWR, 1-2:40pm Trani 250

Instructor: Dan Albrecht-Mallinger

Office: Life Sciences, Room 106

Phone: 807.828.7357


Office Hours: M/W 3-5pm, R 9-11am, or by appointment

Course Dates & Absence Policy: This class runs from 10-June to 18-July. Friday, 14-June is the deadline to submit intended absences for religious observation. Add/drop is 11-June (sorry, not a lot of time there), and the last day to withdraw from the class is 28-June. For an absence to be excused for medical or personal reasons, students must email instructor no later than 24-hours following the absence, with advanced notification strongly preferred. Three unexcused absences will result in the failure of the course.

Texts: All required readings will be available on the course Rampages site as downloadable PDFs. Student library fees are ~$70 per semester. these fees fund the university’s intellectual in fracture, including access to academic databases. Readings for this course will be drawn from library resources.

Hardware & Software:

  • All students are required to bring a functioning laptop to class. If you do not have access to a laptop, contact the instructor to coordinate a semester laptop checkout.
  • All students are required to have Microsoft Office Suite (free to download with your VCU student credentials).
  • All students are required to download and install Program R and RStudio.


Point Breakdown: Assignments will make up 80% of your grade. All assignments are to be submitted to Blackboard; late assignments will be accepted up to 48-hours following the deadline for a flat -10% penalty. Summer Innovation Collaborations (SICs!) will account for the remaining 20% of course grades.

With that boilerplate out of the way, what is this course about?

Thanks for asking! There are 4 goals for this coarse.

  1. To review and learn the foundational concepts in statistics (central tendency, variance, probability, populations, sampling, bias, etc.).
  2. To apply statistical tests to real-world environmental data and draw meaningful inference.
  3. To become proficient in data types, data management, and data analysis in the computing environs of Program R.
  4. To practice collaboration by sharing insights and inquiry.

So what does that actually look like?

We have six weeks to learn a whole lot–and as luck would have it, we are scheduled from 1-2:40pm…our biologically-preset siesta time. In spite of natural inclinations to nap, we will learn a skill, apply that skill, and then critically interpret our applications each session.

You will then be responsible for summarizing the application in a write-up, which will be due before the next class. Most days, you will leave class with a rough draft of the write-up already in hand; ideally, it will only take a single proof-reading before you can submit it.

The majority of our applications will be in Program R, which is a command-line program for statistics and data science. Learning a new programming language is much like learning any other language: you’ll make lots of mistakes, but you’ll learn from them faster through practice with others. A misplaced comma or lowercase letter may stymie you for hours, but a quick glance from a classmate can identify the problem in seconds. Your peer may struggle with a command’s syntax, but you can help talk them through it.

The class will work best when people show up ready to learn and to help one another learn. We’ll be working with a broad set of public environmental data–carbon emissions, lead exposure, biodiversity counts, etc.–and no one will be an expert on everything. You will each have an insight to contribute, so believe in yourself, and believe in one another!

Prospective Schedule: The below table is an outline for topics covered this summer session. These are subject to change based on course conditions.

Day Date Topics
Monday 10-Jun Excel Review; Data Types; Setting up Program R
Tuesday 11-Jun Central Tendency, Variation, and Distributions
Wednesday 12-Jun Probability & Odds Ratios 

Class cancelled due to water outage

Thursday 13-Jun SIC Breakout I: Asking Environmental Questions & Hypothesis Testing

Variance, Probability, & Odds Ratios

Monday 17-Jun Linear Regression & Sum of Least Squares

SIC Breakout I: Asking Environmental Questions & Hypothesis Testing

Tuesday 18-Jun Chi-square & Logistic Regression

Sum of Least Squares, Linear Regression, and Logistic Regression

Wednesday 19-Jun T-tests, ANOVAs, and Chi-Square
Thursday 20-Jun SIC Breakout II: Finding Public Data, [Ethically] Cleaning Public Data
Monday 24-Jun Non-parametric Tests
Tuesday 25-Jun Multiple Regression & Interaction Terms
Wednesday 26-Jun How well does the model fit? Residuals, R2, and Beyond
Thursday 27-Jun SIC Breakout III: Runing Tests on Your Data
Monday 1-Jul Repeated Sampling & Random Effects
Tuesday 2-Jul Spatial & Temporal Autocorrelation
Wednesday 3-Jul Aikike’s Next Top Model
Thursday 4-Jul No class – Independence Day
Monday 8-Jul Prediction from All Manner of Models
Tuesday 9-Jul All the Pretty Plots
Wednesday 10-Jul The Ethical Environmental Statistician
Thursday 11-Jul SIC Breakout IV: Model Comparison & Plotting Your Data
Monday 15-Jul Can You Hack It? The Pollinator Problem
Tuesday 16-Jul Can You Hack It? The #1 Killer
Wednesday 17-Jul Can You Hack It? Sick Breakout V, the Home Stretch
Thursday 18-Jul Final Presentations



DSS: All individuals deserve the opportunity to participate to their fullest capacity at VCU. If you have been diagnosed with a disability, or suspect you may be struggling with a disability, please do not hesitate to communicate with Disability Support Services. If you require accommodations approved by the DSS, you or the DSS office must notify me by email or in person to determine what accommodations will be required for you to succeed in this course, clearly defining student, peer, & instructor expectations.

Respectful Participation: This course will be applications-based, with frequent opportunities to debate and discuss. This does not represent a license to demean, diminish, or ostracize your peers based on their perspective or their person. You do not need to condescend to express skepticism; nor do you need to pillory to disagree. The best way to test ideas is by inquiry: whenever possible, ask questions in lieu of rejecting another’s stance out-of-hand. Above all, address everyone with respect: use the name and pronouns of their preference; 2nd person pronouns are great work-around when you’re unsure of either..


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Full Syllabus Statements

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