Using R For the `beans` data test how effective root biomass (`RtDM`) is as a pr

Question

Using R

For the `beans` data test how effective root biomass (`RtDM`) is as a predictor of root length (`rt.len`)

pot.size phos P.lev rep trt rt.len ShtDM RtDM 4 210 L A a 255.29 0.7962 0.6483 4 210 L B a 211.42 0.779 0.7582 4 210 L C a 265.91 0.9795 0.6995 4 210 L D a 288.55 1.2228 0.989 4 420 H A b 486.6 2.7627 1.751 4 420 H B b 286.06 1.0743 0.6536 4 420 H C b 442.83 2.5355 1.488 4 420 H D b 385.31 1.359 0.849 8 105 L A c 146.18 0.6872 0.5229 8 105 L B c 148.56 0.6004 0.5418 8 105 L C c 167.25 0.8365 0.5874 8 105 L D c 253.51 1.0662 0.7477 8 210 H A d 295.62 1.223 0.9755 8 210 H B d 436.28 0.8157 0.6308 8 210 H C d 521.66 1.4188 1.2314 8 210 H D d 491.56 1.7503 1.1628 12 70 L A e 265.6 1.0496 0.9286 12 70 L B e 159.78 0.513 0.4712 12 70 L C e 212.81 0.7318 0.5258 12 70 L D e 268.84 0.9976 0.8092 12 140 H A f 351.9 1.3016 0.8667 12 140 H B f 274.8 0.8099 0.6846 12 140 H C f 325.41 1.2049 0.9395 12 140 H D f 289.9 1.7439 1.3421

Explanation / Answer

Run the following R code to get the regression equation:

MyData <- read.csv(file="bean.csv", header=TRUE, sep=",")
alli.mod1 = lm(rt.len ~ RtDM, data = MyData)
summary(alli.mod1)

Here' are the results:

We have highlighted the results in bold. Since p-value of this variable is less than .05, we can say that the result is statistically significant.

So, root biomass (`RtDM`) is a good predictor of root length (`rt.len`)

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