Loblolly

How To Create a Barplot

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Category
Visual
Instructional

How To Create a Stacked Barplot

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Visual
Instructional

How To Create a Pie Chart

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Instructional
Visual

How To Compute the Mean

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Category
Numerical
Instructional

How To Create a Plot

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Visual
Instructional

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

Submitted by pmagunia on April 22, 2018 - 3:08 PM
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Cumulative Frequency Histogram

Submitted by pmagunia on April 22, 2018 - 3:09 PM
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Dotplot

Submitted by pmagunia on April 22, 2018 - 3:10 PM
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Hollow Histogram

Submitted by pmagunia on April 22, 2018 - 3:10 PM
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Numerical Summaries

Submitted by pmagunia on April 22, 2018 - 2:51 PM
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Pie Chart

Submitted by pmagunia on April 22, 2018 - 3:11 PM
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Plot

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

Submitted by pmagunia on December 18, 2021 - 4:28 PM

Regression

Submitted by pmagunia on April 22, 2018 - 3:12 PM

Stem and Leaf Plots

Submitted by pmagunia on April 22, 2018 - 3:12 PM
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Visual Summaries

Submitted by pmagunia on April 22, 2018 - 3:13 PM
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Submitted by pmagunia on February 26, 2017 - 11:28 AM
<iframe src="https://embed.picostat.com/loblolly.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-43360.csv 1.03 KB
Documentation

Growth of Loblolly pine trees

The Loblolly data frame has 84 rows and 3 columns of records of the growth of Loblolly pine trees.

Usage

Loblolly

Format

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

height

a numeric vector of tree heights (ft).

age

a numeric vector of tree ages (yr).

Seed

an ordered factor indicating the seed source for the tree. The ordering is according to increasing maximum height.

Details

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

Kung, F. H. (1986), Fitting logistic growth curve with predetermined carrying capacity, in Proceedings of the Statistical Computing Section, American Statistical Association, 340–343.

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

Examples

require(stats); require(graphics)
plot(height ~ age, data = Loblolly, subset = Seed == 329,
     xlab = "Tree age (yr)", las = 1,
     ylab = "Tree height (ft)",
     main = "Loblolly data and fitted curve (Seed 329 only)")
fm1 <- nls(height ~ SSasymp(age, Asym, R0, lrc),
           data = Loblolly, subset = Seed == 329)
age <- seq(0, 30, length.out = 101)
lines(age, predict(fm1, list(age = age)))
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    • Dotplot
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    • Pie Chart
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      1. Frequency Histogram
      2. Relative Frequency Histogram
      3. Cumulative Frequency Histogram
      4. Boxplot (Box-and-whisker plot)
      5. Dotplot
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