R Dataset / Package rpart / cu.summary

How To Create a Barplot

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Visual
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How To Create a Stacked Barplot

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How To Create a Pie Chart

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Visual

How To Compute the Mean

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Numerical
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How To Create a Plot

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How to Compute the Median

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Numerical

Boxplot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
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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

Submitted by pmagunia on December 18, 2021 - 4:28 PM

Regression

Submitted by pmagunia on April 22, 2018 - 3:12 PM

Stem and Leaf Plots

Submitted by pmagunia on April 22, 2018 - 3:12 PM
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Visual Summaries

Submitted by pmagunia on April 22, 2018 - 3:13 PM
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Submitted by pmagunia on March 9, 2018 - 1:06 PM
<iframe src="https://embed.picostat.com/r-dataset-package-rpart-cusummary.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-90446.csv 5.9 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 cu.summary data set which pertains to Automobile Data from 'Consumer Reports' 1990. The cu.summary data set is found in the rpart R package. Try to load the cu.summary data set in R by issuing the following command at the console data("cu.summary"). This may load the data into a variable called cu.summary. If R says the cu.summary data set is not found, you can try installing the package by issuing this command install.packages("rpart") and then attempt to reload the data with library("rpart") followed by data("cu.summary"). 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 cu.summary 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 cu.summary R data set. The size of this file is about 6,046 bytes.


Automobile Data from 'Consumer Reports' 1990

Description

The cu.summary data frame has 117 rows and 5 columns, giving data on makes of cars taken from the April, 1990 issue of Consumer Reports.

Usage

cu.summary

Format

This data frame contains the following columns:

Price

a numeric vector giving the list price in US dollars of a standard model

Country

of origin, a factor with levels Brazil, England, France, Germany, Japan, Japan/USA, Korea, Mexico, Sweden and USA

Reliability

an ordered factor with levels Much worse < worse < average < better < Much better

Mileage

fuel consumption miles per US gallon, as tested.

Type

a factor with levels Compact Large Medium Small Sporty Van

Source

Consumer Reports, April, 1990, pp. 235–288 quoted in

John M. Chambers and Trevor J. Hastie eds. (1992) Statistical Models in S, Wadsworth and Brooks/Cole, Pacific Grove, CA, pp. 46–47.

See Also

car.test.frame, car90

Examples

fit <- rpart(Price ~ Mileage + Type + Country, cu.summary)
par(xpd = TRUE)
plot(fit, compress = TRUE)
text(fit, use.n = TRUE)

--

Dataset imported from https://www.r-project.org.
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How To Perform Statistical Analysis with Picostat
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  2. Near the top of the page there will be two drop downs. One for analysis and one for education. Here we will choose Analyis. Choose from one of the following:
    • Numerical Summaries - Here you can get the:
      1. Arithmetic mean
      2. Median
      3. Quartiles
      4. Minimum and Maximum
      5. Stem-and-leaf plot
      6. Standard deviation and Variance
      7. IQR
      8. Cumulative frequencies
    • Plot - a plot of two columns on the cartesian coordinate system
    • Boxplot - a Boxplot (box-and-whisker plot) of a column.
    • Correlation Coefficient - Compute the correlation coefficient between two columns.
    • Cumulative Frequency Histogram - Display a cumulative frequency histogram
    • Dotplot
    • Hollow Histogram - Plot two columns on the same histogram with a different color for each column.
    • Pie Chart
    • Regression - Perform a simple linear regression and compute the p-value and regression line. Also plots the data with the regression line.
    • Stem and Leaf Plots - Plot a one or two-sided stem-and-leaf plot from one or two columns respectively.
    • Visual Summaries - plots the following:
      1. Frequency Histogram
      2. Relative Frequency Histogram
      3. Cumulative Frequency Histogram
      4. Boxplot (Box-and-whisker plot)
      5. Dotplot
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  2. Near the top of the page there will be two drop downs. One for analysis and one for education. Here we will choose Education. Choose from one of the following:
    • How To Create a Barplot - This will show you how to create a bar chart after selecting a column with the mouse.
    • How To Create a Stacked Barplot - This application will show you how to create a stacked bar plot from a column vector.
    • How To Create a Pie Chart - This application will show you how to create a pie chart from a column of data
    • How To Compute the Mean - This application will show you how to compute the mean from a column vector
    • How To Create a Plot - This app will show you how to plot two columns in the cartesian coordinate system.
    • How To Compute the Media - This statisistical app will show you how to compute the median from a column vector.
  3. PDF - Check this box if you want to download a PDF of the output from the education application.
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