CO2

How To Create a Barplot

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Visual
Instructional

How To Create a Stacked Barplot

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How To Create a Pie Chart

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Visual

How To Compute the Mean

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Numerical
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How To Create a Plot

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How to Compute the Median

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Numerical

Boxplot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
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Correlation Coefficient

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Cumulative Frequency Histogram

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Dotplot

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Hollow Histogram

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Numerical Summaries

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Pie Chart

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Plot

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Regression

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Stem and Leaf Plots

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Visual Summaries

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Submitted by pmagunia on February 26, 2017 - 11:28 AM
<iframe src="https://embed.picostat.com/co2.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-23612.csv 3.14 KB
Documentation

Carbon Dioxide Uptake in Grass Plants

The CO2 data frame has 84 rows and 5 columns of data from an experiment on the cold tolerance of the grass species Echinochloa crus-galli.

Usage

CO2

Format

An object of class c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame") containing the following columns:

Plant

an ordered factor with levels Qn1 < Qn2 < Qn3 < ... < Mc1 giving a unique identifier for each plant.

Type

a factor with levels Quebec Mississippi giving the origin of the plant

Treatment

a factor with levels nonchilled chilled

conc

a numeric vector of ambient carbon dioxide concentrations (mL/L).

uptake

a numeric vector of carbon dioxide uptake rates (umol/m^2 sec).

Details

The CO2 uptake of six plants from Quebec and six plants from Mississippi was measured at several levels of ambient CO2 concentration. Half the plants of each type were chilled overnight before the experiment was conducted.

This dataset was originally part of package nlme, and that has methods (including for [, as.data.frame, plot and print) for its grouped-data classes.

Source

Potvin, C., Lechowicz, M. J. and Tardif, S. (1990) “The statistical analysis of ecophysiological response curves obtained from experiments involving repeated measures”, Ecology, 71, 1389–1400.

Pinheiro, J. C. and Bates, D. M. (2000) Mixed-effects Models in S and S-PLUS, Springer.

Examples

require(stats); require(graphics)

coplot(uptake ~ conc | Plant, data = CO2, show.given = FALSE, type = "b")
## fit the data for the first plant
fm1 <- nls(uptake ~ SSasymp(conc, Asym, lrc, c0),
   data = CO2, subset = Plant == "Qn1")
summary(fm1)
## fit each plant separately
fmlist <- list()
for (pp in levels(CO2$Plant)) {
  fmlist[[pp]] <- nls(uptake ~ SSasymp(conc, Asym, lrc, c0),
      data = CO2, subset = Plant == pp)
}
## check the coefficients by plant
print(sapply(fmlist, coef), digits = 3)
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