In this activity, we will continue to work with the water quality data, working on more summary tables and analyses.

To complete this activity, you will submit:

  1. Code. Keep a good record of the code you use to complete this activity. In your R script, take notes (using the # sign) to describe what you are doing.
  2. A summary: Record your observations and findings in a google document. In your gogle document, you can copy the figures you make and describe your results in each part of the activity.
  3. Code Questions: Write down any questions that you have about the data.
  4. Next steps: Reflect on what else you could explore using the water quality data. Write up a paragraph describe what you think you could do next. These next steps should be do-able and realistic for our class.
  5. Submit the code and the summary file in the initial code and questions file in Moodle.

First, go ahead and read in your water quality data file from where ever you have it saved.

wq <- read.csv('data/raleigh_water_analysis.csv')

Summarizing sites

First, we will work on look at the differences among the different sites. In groups, have each group member pick a different stream metric to explore.

  1. Use a summary table to determine how the sites differ with respect to your chosen metric (ex. total nitrogen, dissolved oxygen etc.)
  2. Make a boxplot to show the differences between the sites.
  3. Share your results with your group members. Do you notice any similarities or diffences when comparing with your group members?

Need help with summary tables? Review the lesson on summary tables and the activity we did last class.

Summarizing over time

Next, let’s look at how water quality has changed over the years in Raleigh. In groups, have each group member pick a different stream metric to explore.

  1. Use what you learned in the advanced R lesson on dates to make a new column with the year that water quality was measured.
  2. Make a summary table summaries the water quality metric for each year. Arrange the summary table in order of years.
  3. Make a line graph showing the the metric you chose over the years. There are different ways that you can make this graph (with each site it’s own line or a summary of all sites).
  4. Share your results with your group.

Precipitation

Next, we will look at how precipitation values can impact the water quality measurements.

  1. Go back to your advanced R homework, where you joined the precipiation data with the water quality data and explored the relationship between turbidity and precipitation. What did you notice about the relationship?
  2. Analyze the relationship between turbidity and precipitation with a statistical test (lm())
  3. Write up a summary of your results.
  4. In your group, each person should pick one other metric to observe to see if it is effected by precipitation.
  5. Use a statistical test to see if there is a relationship between the metric you chose and precipitation.
  6. Make a pretty figure to show your result.
  7. Write a figure caption to summarize your result.
  8. Share your results with your group.