Logging and Water Quality
Data from an observational study of nitrate levels measured at three week intervals for five years in two watersheds. One of the watersheds was undisturbed and the other had been logged with a patchwork pattern.
case1501
A data frame with 88 observations on the following 3 variables.
Weekweek after the start of the study
Patchresidual nitrate level in the logged watershed (ppm) (see Display 15.3 of Statistical Sleuth)
Nocutresidual nitrate level in the undisturbed watershed (ppm)
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.
Harr, R.D., Friderksen, R.L., and Rothacher, J. (1979). Changes in Streamflow Following Timber Harvests in Southwestern Oregon, USDA/USFS Research Paper PNW-249, Pacific NW Forest and Range Experiment Station, Portland, Oregon.
str(case1501) par(mfrow=c(2,1)) # Make 2 plots on one page plot(Nocut ~ Week, case1501) plot(Patch ~ Week, case1501) par(mfrow=c(1,1)) lag.plot(case1501$Nocut,do.lines=FALSE) lag.plot(case1501$Patch,do.lines=FALSE) # Compute pooled estimate of first autocorrelation coefficient # First auto covariance, Nocut ac1nocut <- acf(case1501$Nocut,lag.max=1,type="covariance",plot=FALSE)$acf[2] n <- length(case1501$Nocut) # Zeroth autocovariance for Nocut ac0nocut <- var(case1501$Nocut[2:n])*(n-2)/(n-1) # First auto covariance, Patch ac1patch <- acf(case1501$Patch,lag.max=1,type="covariance",plot=FALSE)$acf[2] # Zeroth autocovariance for PATCH ac0patch <- var(case1501$Patch [2:n])*(n-2)/(n-1) ac1pool <- (ac1nocut + ac1patch)/2 ac0pool <- (ac0nocut + ac0patch)/2 acorr1 <- ac1pool/ac0pool acorr1 # Pooled estimate of first lag serial coefficient
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.