# Rubric

1. (2 p) Read and plot data, with $$x$$ = Avg_Mercury vs $$y$$ = Alkalinity.

2. (1 p) Describe the relationship you see.

3. (3 p) Determine an appropriate transformation of the $$x$$-variable, $$y$$-variable, or both in order to have a straight-line relationship.

4. (1 p) Plot the data on the transformed scale If you want to make 3 more plots, then choose the one you want to interpret, that will be fine. Consider $$(\log(x), y)$$, $$(x,\log(y))$$, and $$(\log(x), \log(y))$$.

5. (3 p) Interpret the slope on the transformed scale.

Add to this file under the appropriate subsections below, then submit your results to UNM Learn …

## 1. Read and plot data

dat <- read.table("ADA1_WS_10_Data-FishMercury.txt", skip = 25, header = TRUE)
str(dat)
## 'data.frame':    53 obs. of  12 variables:
##  $ID : int 1 2 3 4 5 6 7 8 9 10 ... ##$ Lake                  : Factor w/ 53 levels "Alligator","Annie",..: 1 2 3 4 5 6 7 8 9 10 ...
##  $Alkalinity : num 5.9 3.5 116 39.4 2.5 19.6 5.2 71.4 26.4 4.8 ... ##$ pH                    : num  6.1 5.1 9.1 6.9 4.6 7.3 5.4 8.1 5.8 6.4 ...
##  $Calcium : num 3 1.9 44.1 16.4 2.9 4.5 2.8 55.2 9.2 4.6 ... ##$ Chlorophyll           : num  0.7 3.2 128.3 3.5 1.8 ...
##  $Avg_Mercury : num 1.23 1.33 0.04 0.44 1.2 0.27 0.48 0.19 0.83 0.81 ... ##$ No.samples            : int  5 7 6 12 12 14 10 12 24 12 ...
##  $min : num 0.85 0.92 0.04 0.13 0.69 0.04 0.3 0.08 0.26 0.41 ... ##$ max                   : num  1.43 1.9 0.06 0.84 1.5 0.48 0.72 0.38 1.4 1.47 ...
##  $X3_yr_Standard_Mercury: num 1.53 1.33 0.04 0.44 1.33 0.25 0.45 0.16 0.72 0.81 ... ##$ age_data              : int  1 0 0 0 1 1 1 1 1 1 ...

Plot $$x$$ = Avg_Mercury vs $$y$$ = Alkalinity on their natural (original) scales.