R Dataset / Package datasets / longley

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Cumulative Frequency Histogram

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Plot

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Attachment	Size
dataset-70074.csv	792 bytes

Dataset License

GNU General Public License v2.0

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GNU General Public License v2.0

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Dataset Help
On this Picostat.com statistics page, you will find information about the longley data set which pertains to Longley's Economic Regression Data. The longley data set is found in the datasets R package. You can load the longley data set in R by issuing the following command at the console data("longley"). This will load the data into a variable called longley. If R says the longley data set is not found, you can try installing the package by issuing this command install.packages("datasets") 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 longley R data set. The size of this file is about 792 bytes.

Dataset Help

On this Picostat.com statistics page, you will find information about the longley data set which pertains to Longley's Economic Regression Data. The longley data set is found in the datasets R package. You can load the longley data set in R by issuing the following command at the console data("longley"). This will load the data into a variable called longley. If R says the longley data set is not found, you can try installing the package by issuing this command install.packages("datasets") 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 longley R data set. The size of this file is about 792 bytes.

Documentation

Documentation
Longley's Economic Regression Data Description A macroeconomic data set which provides a well-known example for a highly collinear regression. Usage longley Format A data frame with 7 economical variables, observed yearly from 1947 to 1962 (n=16). `GNP.deflator` GNP implicit price deflator (1954=100) `GNP` Gross National Product. `Unemployed` number of unemployed. `Armed.Forces` number of people in the armed forces. `Population` ‘noninstitutionalized’ population ≥ 14 years of age. `Year` the year (time). `Employed` number of people employed. The regression `lm(Employed ~ .)` is known to be highly collinear. Source J. W. Longley (1967) An appraisal of least-squares programs from the point of view of the user. Journal of the American Statistical Association 62, 819–841. References Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole. Examples require(stats); require(graphics) ## give the data set in the form it is used in S-PLUS: longley.x <- data.matrix(longley[, 1:6]) longley.y <- longley[, "Employed"] pairs(longley, main = "longley data") summary(fm1 <- lm(Employed ~ ., data = longley)) opar <- par(mfrow = c(2, 2), oma = c(0, 0, 1.1, 0), mar = c(4.1, 4.1, 2.1, 1.1)) plot(fm1) par(opar) -- Dataset imported from https://www.r-project.org.

Longley's Economic Regression Data

Description

A macroeconomic data set which provides a well-known example for a highly collinear regression.

Usage

longley

Format

A data frame with 7 economical variables, observed yearly from 1947 to 1962 (n=16).

GNP.deflator: GNP implicit price deflator (1954=100)
GNP: Gross National Product.
Unemployed: number of unemployed.
Armed.Forces: number of people in the armed forces.
Population: ‘noninstitutionalized’ population ≥ 14 years of age.
Year: the year (time).
Employed: number of people employed.

The regression lm(Employed ~ .) is known to be highly collinear.

Source

J. W. Longley (1967) An appraisal of least-squares programs from the point of view of the user. Journal of the American Statistical Association 62, 819–841.

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

Examples

require(stats); require(graphics)
## give the data set in the form it is used in S-PLUS:
longley.x <- data.matrix(longley[, 1:6])
longley.y <- longley[, "Employed"]
pairs(longley, main = "longley data")
summary(fm1 <- lm(Employed ~ ., data = longley))
opar <- par(mfrow = c(2, 2), oma = c(0, 0, 1.1, 0),
            mar = c(4.1, 4.1, 2.1, 1.1))
plot(fm1)
par(opar)

--

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

Curated Data	File Size
OpenIntro Statistics Dataset - yrbss_samp	7.62 KB
OpenIntro Statistics Dataset - yrbss	1.03 MB
OpenIntro Statistics Dataset - yawn	861 bytes
OpenIntro Statistics Dataset - xom	4.95 KB
OpenIntro Statistics Dataset - winery_cars	489 bytes

All Public Datasets	File Size
PSID
wage1	328 bytes
OpenIntro Statistics Dataset - yrbss_samp	7.62 KB
OpenIntro Statistics Dataset - yrbss	1.03 MB
OpenIntro Statistics Dataset - yawn	861 bytes

R Output	Date
Picostat Output - Boxplot	Feb 2, 2020
Picostat Output - Boxplot	Feb 2, 2020
Picostat Output - Boxplot	Feb 2, 2020
Picostat Output - Boxplot	Feb 2, 2020
Picostat Output - Boxplot	Feb 2, 2020

Recent Queries	App/Dataset	By	Date
Picostat Output - Numerical Summaries	R Dataset / Package datasets / quakes	wicetram	October 24, 2020 - 3:20 PM
Picostat Output - Visual Summaries	R Dataset / Package datasets / quakes	wicetram	October 24, 2020 - 3:17 PM
Picostat Output - Visual Summaries	R Dataset / Package datasets / quakes	wicetram	October 24, 2020 - 3:15 PM
Picostat Output - Cumulative Frequency Histogram	R Dataset / Package datasets / quakes	wicetram	October 24, 2020 - 3:12 PM
Picostat Output - Boxplot	R Dataset / Package datasets / quakes	wicetram	October 24, 2020 - 3:12 PM

PICOSTAT

R Dataset / Package datasets / longley

How To Create a Barplot

How To Create a Stacked Barplot

How To Create a Pie Chart

How To Compute the Mean

How To Create a Plot

How to Compute the Median

Boxplot

Correlation Coefficient

Cumulative Frequency Histogram

Dotplot

Hollow Histogram

Numerical Summaries

Pie Chart

Plot

Regression

Stem and Leaf Plots

Visual Summaries

Longley's Economic Regression Data

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