# R Dataset / Package psych / burt

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## Visual Summaries

Embed
<iframe src="https://embed.picostat.com/r-dataset-package-psych-burt.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
746 bytes
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 burt data set which pertains to 11 emotional variables from Burt (1915). The burt data set is found in the psych R package. You can load the burt data set in R by issuing the following command at the console data("burt"). This will load the data into a variable called burt. If R says the burt data set is not found, you can try installing the package by issuing this command install.packages("psych") 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 burt R data set. The size of this file is about 746 bytes.

Documentation

## 11 emotional variables from Burt (1915)

### Description

Cyril Burt reported an early factor analysis with a circumplex structure of 11 emotional variables in 1915. 8 of these were subsequently used by Harman in his text on factor analysis. Unfortunately, it seems as if Burt made a mistake for the matrix is not positive definite. With one change from .87 to .81 the matrix is positive definite.

### Usage

data(burt)

### Format

A correlation matrix based upon 172 "normal school age children aged 9-12".

Sociality

Sociality

Sorrow

Sorrow

Tenderness

Tenderness

Joy

Joy

Wonder

Wonder

Elation

Elation

Disgust

Disgust

Anger

Anger

Sex

Sex

Fear

Fear

Subjection

Subjection

### Details

The Burt data set is interesting for several reasons. It seems to be an early example of the organizaton of emotions into an affective circumplex, a subset of it has been used for factor analysis examples (see Harman.Burt, and it is an example of how typos affect data. The original data matrix has one negative eigenvalue. With the replacement of the correlation between Sorrow and Tenderness from .87 to .81, the matrix is positive definite.

Alternatively, using cor.smooth, the matrix can be made positive definite as well, although cor.smooth makes more (but smaller) changes.

### Source

(retrieved from the web at http://www.biodiversitylibrary.org/item/95822#790) Following a suggestion by Jan DeLeeuw.

### References

Burt, C.General and Specific Factors underlying the Primary Emotions. Reports of the British Association for the Advancement of Science, 85th meeting, held in Manchester, September 7-11, 1915. London, John Murray, 1916, p. 694-696 (retrieved from the web at http://www.biodiversitylibrary.org/item/95822#790)

### See Also

Harman.Burt in the Harman dataset and cor.smooth

### Examples

data(burt)
eigen(burt)$values #one is negative! burt.new <- burt burt.new[2,3] <- burt.new[3,2] <- .81 eigen(burt.new)$values  #all are positive
bs <- cor.smooth(burt)
round(burt.new - bs,3)
--

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

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