Plant Water Data with R
1
Prerequisites
1.1
R, RStudio, and the tidyverse
1.2
Colophon
2
Introduction to R, RStudio, and the tidyverse
3
Flow data and the concept of loading
4
Sampling and measurements
5
Laboratory analysis and data management
6
Descriptive statistics: numerical methods for describing monitoring data
7
Descriptive statistics: graphical methods for describing monitoring data
8
Removal efficiencies
9
Symmetry and asymmetry in monitoring data: normal and log-normal distributionss
10
Compliance with targets and regulatory standards for effluents and water bodies
11
Making comparisons with your monitoring data: tests of hypotheses
12
Relationship between monitoring variables: correlation and regression analysis
13
Water and mass balances
14
Loading rates applied to treatment units
15
Reaction kinetics and reactor hydraulics
16
Model application, calibration, and verification
References
Published with bookdown
Assessment of Treatment Plant Performance and Water Quality Data using R, RStudio, and the tidyverse
Chapter 2
Introduction to R, RStudio, and the tidyverse
Need to cover
ggplot2 (basics of)
dplyr + the pipe (at least select and mutate)
workflow (RStudio, RMarkdown)