R Dataset / Package boot / acme

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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Regression

Stem and Leaf Plots

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Visual Summaries

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Attachment Size
dataset-59091.csv 1.59 KB
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
R Dataset Help

On this Picostat.com statistics page, you will find information about the acme data set which pertains to Monthly Excess Returns. The acme data set is found in the boot R package. You can load the acme data set in R by issuing the following command at the console data("acme"). This will load the data into a variable called acme. If R says the acme data set is not found, you can try installing the package by issuing this command install.packages("boot") 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 acme R data set. The size of this file is about 1,624 bytes.

Documentation

Monthly Excess Returns

Description

The acme data frame has 60 rows and 3 columns.

The excess return for the Acme Cleveland Corporation are recorded along with those for all stocks listed on the New York and American Stock Exchanges were recorded over a five year period. These excess returns are relative to the return on a risk-less investment such a U.S. Treasury bills.

Usage

acme

Format

This data frame contains the following columns:

month

A character string representing the month of the observation.

market

The excess return of the market as a whole.

acme

The excess return for the Acme Cleveland Corporation.

Source

The data were obtained from

Simonoff, J.S. and Tsai, C.-L. (1994) Use of modified profile likelihood for improved tests of constancy of variance in regression. Applied Statistics, 43, 353–370.

References

Davison, A.C. and Hinkley, D.V. (1997) Bootstrap Methods and Their Application. Cambridge University Press.

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

All Public Datasets File Size
Test 394 bytes
Q1 332 bytes
prova_Correlatio 593 bytes
profva
test 332 bytes