Description

In this lesson, users play the role of a fisheries biologist tasked with monitoring the run-strength of Atlantic River Herring in a tributary of the Chesapeake Bay. Users will learn how to visibly assess and present data by constructing plots with ggplot, test for data normality using a Shapiro-Wilk normality test, perform data transformations in R Studio, and conduct a nonparametric statistical analysis by using a Paired Samples Wilcoxon Signed Rank Test. Along the way, students will be exposed to contemporary fisheries science topics, and use their acquired skills to answer questions related to the ecological and quantitative concepts covered within the lesson.

To assist with this, users should download and review the associated components from this resource package. The creator of this lesson recommends downloading and reviewing the documents in the following order:

1.) RHerringBackground.mp4 - provides a high-level synopsis of the ecological backstory, quantitative lesson, and data sources for this resource.

2.) RHerringBackground_Instructor and/or RHerringBackground_Student - contains relevant ecological and methodological background information for the quantitative R Studio lesson.

3.) RHerringLesson.RMD + TrapDataV2.xlsx + DailyCounts_20.xlsx – this is the interactive quantitative lesson that can be executed using R Studio. These files need to be downloaded into the same folder. Please double-check that your downloaded file names match these.

4.) RHerringLesson.html – this is an alternative method of letting students experience the quantitative portion of the lesson – without needing to use R Studio.

Cite this work