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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,37 @@ | ||
| # Nathan Kroeze | ||
| # Exercise 9 | ||
| # 11/18/2022 | ||
|
|
||
| library(tidyverse) | ||
|
|
||
| # Q1: Enter those data into a text file or Excel and then | ||
| # save a text file, and write a script that loads this text file and produces a scatter plot of those two variables | ||
| # that includes a trend line. | ||
|
|
||
| setwd("C:/Users/Natha/Desktop/Biocomputing/Exercise09/") | ||
| researchData <- read.csv("researchData.csv") | ||
| researchData <- researchData[,-1] #remove count column | ||
|
|
||
| ggplot(researchData, aes(d13C,d15N)) + | ||
| geom_jitter() + geom_smooth(method = "lm") + | ||
| labs(title = "Research Isotope Data") | ||
|
|
||
| # Q2: Write a script that generates two figures that sumamrize the data. First, show | ||
| # a barplot of the means of the four populations. Second, show a scatter plot of all of the observations. | ||
|
|
||
| dataEx <- read.table("data.txt",header = TRUE, sep = ",") | ||
|
|
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| ggplot(data = dataEx, aes(x=region,y=observations)) + | ||
| stat_summary(geom = "bar",fun = "mean") + | ||
| xlab("Region") + ylab("Means of Populations") + theme_bw() | ||
|
|
||
| ggplot(data = dataEx, aes(x=region,y=observations)) + | ||
| geom_jitter() + | ||
| xlab("Region") + ylab("Observations") + theme_bw() | ||
|
|
||
| # Answers: | ||
| # The plots tell different stories because the bar plot demonstrates that the average population for | ||
| # each region is roughly the same, however the scatter plot shows that the variance in these data are not | ||
| # consistent across regions. For example, the western region has a wide variance of observations but | ||
| # the northern region has a narrow densely populated band. This difference is lost in the bar plot and | ||
| # would have been missed if not plotted separately. | ||
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| "d15N" "d13C" | ||
| "1" 5.3 -28.9 | ||
| "2" 4 -28.8 | ||
| "3" 3.1 -28.8 | ||
| "4" 3.5 -25.1 | ||
| "5" 3.1 -27.1 | ||
| "6" 3.2 -28.1 | ||
| "7" 2.2 -28.1 | ||
| "8" 3 -27.4 | ||
| "9" 2.4 -28.7 | ||
| "10" 3 -26.2 | ||
| "11" 3 -26.7 | ||
| "12" 3.1 -27.4 | ||
| "13" 4.5 -26.4 | ||
| "14" 3.3 -27.8 | ||
| "15" 3.3 -28.5 | ||
| "16" 3.2 -27.3 | ||
| "17" 3 -26.4 | ||
| "18" 3 -27.4 | ||
| "19" 2.8 -22.7 | ||
| "20" 3.9 -23.3 | ||
| "21" 3.4 -22.4 | ||
| "22" 3.7 -28 | ||
| "23" 3.6 -28.8 | ||
| "24" 3.3 -28.4 | ||
| "25" 5.3 -28 | ||
| "26" 3.5 -28.2 | ||
| "27" 3.5 -29.1 | ||
| "28" 3.1 -28.8 | ||
| "29" 3.2 -28.9 | ||
| "30" 2.9 -29 | ||
| "31" 4.2 -20.3 | ||
| "32" 4.2 -22.6 | ||
| "33" 4.4 -24.4 | ||
| "34" 2.8 -26.6 | ||
| "35" 2.8 -28.4 | ||
| "36" 3.1 -28.5 | ||
| "37" 5 -27.5 | ||
| "38" 3.7 -26.1 | ||
| "39" 2.7 -28.5 | ||
| "40" 2.5 -28.9 | ||
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| "42" 2.1 -28.9 | ||
| "43" 1.2 -26.8 | ||
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| "45" 2.2 -28.3 | ||
| "46" 3.6 -15.9 | ||
| "47" 3.8 -16.8 | ||
| "48" 3 -22.3 | ||
| "49" 5.5 -24.7 | ||
| "50" 3.6 -26.7 | ||
| "51" 3 -27.2 | ||
| "52" 3.5 -28.1 | ||
| "53" 3 -28.6 | ||
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| "63" 3.8 -28.1 | ||
| "64" 3.9 -26.4 | ||
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| "121" 3.3 -28 | ||
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| "124" 3.5 -27.8 | ||
| "125" 3.3 -30.7 | ||
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| "127" 3.2 -27 | ||
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| "135" 4 -28.3 | ||
| "136" 3.1 -23 | ||
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| "139" 2.9 -25.4 | ||
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| "150" 3.5 -27 | ||
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| "193" 2.9 -30.1 | ||
| "194" 3.8 -30.3 | ||
| "195" 3.3 -30.1 | ||
| "196" 3 -29.8 | ||
| "197" 4.4 -29.5 | ||
| "198" 2.9 -29.4 | ||
| "199" 3.4 -14.5 | ||
| "200" 3.2 -13.9 | ||
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| "202" 2.3 -29.8 | ||
| "203" 2 -30 | ||
| "204" 1.4 -29.2 | ||
| "205" 3.4 -13.9 | ||
| "206" 2.3 -13.4 | ||
| "207" 1.9 -13.6 | ||
| "208" 1.5 -29.6 | ||
| "209" 3 -30.2 | ||
| "210" 1.3 -29.6 | ||
| "211" 4 -14.5 | ||
| "212" 3.3 -14.1 | ||
| "213" 3 -14.2 | ||
| "214" 3.1 -29.5 | ||
| "215" 2.9 -31.2 | ||
| "216" 3.3 -13.9 | ||
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| "219" 3.8 -14.3 | ||
| "220" 2.3 -29.5 | ||
| "221" 5.2 -29.6 | ||
| "222" 4.7 -14.1 | ||
| "223" 2.6 -29.8 | ||
| "224" 2.1 -29.4 | ||
| "225" 2.7 -28.7 | ||
| "226" 3.6 -30.2 | ||
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| "228" 2.1 -28.7 | ||
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| "232" 3.5 -14.2 | ||
| "233" 3.5 -29 | ||
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| "241" 3 -28.1 |
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I don't know why you used a jitter plot hear