1. How to plot x-y data and put statistics analysis on GLEON Fellowship Workshop January 14-18, 2013 Sunapee, NH Ari Santoso

2. Linear regression It is an example of how to plot (x-y, scattered) our data and do linear regression analysis of the data It starts from up loading the *.txt data into R, manipulate the data, and ends up with statistics and plots

3. Skill relevance/usefulness At a glance, R is complicated, but truly not after we dig in to it. Running R and its scripts is a good practice and start for being familiar with command line functions programming e.g. DYRSYM- CAEDYM. We can go to help() for hints, or google in its website (http://cran.r-project.org/) or in youtubehttp://cran.r-project.org/

4. Application to data I used pCO2 data from 12 Rotorua lakes NZ from 2002-2010 period Main challenges…(R it self… ) – Scripting (not friendly “click and play” GUI) – Not an easy to understand Manuals – Labeling the plot

5. Results > names(Rotorua) [1] "Lake" "Date" "Ts" "pCO2s" "Tb" "pCO2b"

6. Residuals: Min 1Q Median 3Q Max -1694.06 -148.65 -43.53 97.25 2256.66 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 236.39062 29.15935 8.107 5.93e-15 *** exRmmix$pCO2b 0.59465 0.03252 18.286 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 308.2 on 414 degrees of freedom Multiple R-squared: 0.4468, Adjusted R-squared: 0.4455 F-statistic: 334.4 on 1 and 414 DF, p-value: < 2.2e-16 Residuals: Min 1Q Median 3Q Max -1183.6 -366.4 -171.4 169.9 8747.6 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 532.02876 42.00579 12.666 < 2e-16 *** exRmstr$pCO2b 0.07505 0.01473 5.095 4.47e-07 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 790.5 on 714 degrees of freedom Multiple R-squared: 0.03508, Adjusted R-squared: 0.03373 F-statistic: 25.96 on 1 and 714 DF, p-value: 4.47e-07