R Dataset / Package DAAG / progression

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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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<iframe src="https://embed.picostat.com/r-dataset-package-daag-progression.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-89251.csv 6.89 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Dataset Help

On this Picostat.com statistics page, you will find information about the progression data set which pertains to Progression of Record times for track races, 1912 - 2008. The progression data set is found in the DAAG R package. You can load the progression data set in R by issuing the following command at the console data("progression"). This will load the data into a variable called progression. If R says the progression data set is not found, you can try installing the package by issuing this command install.packages("DAAG") and then attempt to reload the data. 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 progression R data set. The size of this file is about 7,054 bytes.

Documentation

Progression of Record times for track races, 1912 - 2008

Description

Progression in world record times for track and road races.

Usage

data(progression)

Format

A data frame with 227 observations on the following 4 columns.

year

Year that time was first recorded

Distance

distance in kilometers

Time

time in minutes

race

character; descriptor for event (100m, mile, ...)

Details

Record times for men's track events, from 1912 onwards. The series starts with times that were recognized as record times in 1912, where available.

Source

Links to sources for the data are at

http://en.wikipedia.org/wiki/Athletics_world_record

Examples

data(progression)
plot(log(Time) ~ log(Distance), data=progression)
xyplot(log(Time) ~ log(Distance), data=progression, type=c("p","r"))
xyplot(log(Time) ~ log(Distance), data=progression,
       type=c("p","smooth"))
res <- resid(lm(log(Time) ~ log(Distance), data=progression))
plot(res ~ log(Distance), data=progression,
     ylab="Residuals from regression line on log scales")
--

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

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