R Dataset / Package COUNT / loomis

How To Create a Barplot

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How To Create a Stacked Barplot

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How To Create a Pie Chart

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How To Compute the Mean

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How To Create a Plot

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How to Compute the Median

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Boxplot

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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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Ratio

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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 March 9, 2018 - 1:06 PM
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Attachment Size
dataset-14247.csv 9.46 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Documentation

On this Picostat.com statistics page, you will find information about the loomis data set which pertains to loomis. The loomis data set is found in the COUNT R package. Try to load the loomis data set in R by issuing the following command at the console data("loomis"). This may load the data into a variable called loomis. If R says the loomis data set is not found, you can try installing the package by issuing this command install.packages("COUNT") and then attempt to reload the data with library("COUNT") followed by data("loomis"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing loomis at the command-line which should display the entire dataset.

If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the loomis R data set. The size of this file is about 9,685 bytes.


loomis

Description

Data are taken from Loomis (2003). The study relates to a survey taken on reported frequency of visits to national parks during the year. The survey was taken at park sites, thus incurring possible effects of endogenous stratification.

Usage

data(loomis)

Format

A data frame with 410 observations on the following 11 variables.

anvisits

number of annual visits to park

gender

1=male;0=female

income

income in US dollars per year, categorical: 4 levels

income1

<=$25000

income2

>$25000 - $55000

income3

>$55000 - $95000

income4

>$95000

travel

travel time, categorical: 3 levels

travel1

<.25 hrs

travel2

>=.25 - <4 hrs

travel3

>=4 hrs

Details

loomis is saved as a data frame. Count models typically use anvisits as response variable. 0 counts are included

Source

from Loomis (2003)

References

Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press Loomis, J. B. (2003). Travel cost demand model based river recreation benefit estimates with on-site and household surveys: Comparative results and a correction procedure, Water Resources Research, 39(4): 1105

Examples

data(loomis)
glmlmp <- glm(anvisits ~ gender + factor(income) + factor(travel), family=poisson, data=loomis)
summary(glmlmp)
exp(coef(glmlmp))
library(MASS)
glmlmnb <- glm.nb(anvisits ~ gender + factor(income) + factor(travel), data=loomis)
summary(glmlmnb)
exp(coef(glmlmnb))

--

Dataset imported from https://www.r-project.org.
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