R Dataset / Package MASS / Pima.te

How To Create a Barplot

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Category
Visual
Instructional

How To Create a Stacked Barplot

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Visual
Instructional

How To Create a Pie Chart

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Instructional
Visual

How To Compute the Mean

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Category
Numerical
Instructional

How To Create a Plot

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Category
Visual
Instructional

How to Compute the Median

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Instructional
Numerical

Boxplot

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

Submitted by pmagunia on April 22, 2018 - 3:08 PM
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Cumulative Frequency Histogram

Submitted by pmagunia on April 22, 2018 - 3:09 PM
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Dotplot

Submitted by pmagunia on April 22, 2018 - 3:10 PM
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Hollow Histogram

Submitted by pmagunia on April 22, 2018 - 3:10 PM
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Numerical Summaries

Submitted by pmagunia on April 22, 2018 - 2:51 PM
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Pie Chart

Submitted by pmagunia on April 22, 2018 - 3:11 PM
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Plot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
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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-mass-pimate.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-60851.csv 10.02 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 Pima.te data set which pertains to Diabetes in Pima Indian Women. The Pima.te data set is found in the MASS R package. Try to load the Pima.te data set in R by issuing the following command at the console data("Pima.te"). This may load the data into a variable called Pima.te. If R says the Pima.te data set is not found, you can try installing the package by issuing this command install.packages("MASS") and then attempt to reload the data with library("MASS") followed by data("Pima.te"). 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 Pima.te 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 Pima.te R data set. The size of this file is about 10,259 bytes.


Diabetes in Pima Indian Women

Description

A population of women who were at least 21 years old, of Pima Indian heritage and living near Phoenix, Arizona, was tested for diabetes according to World Health Organization criteria. The data were collected by the US National Institute of Diabetes and Digestive and Kidney Diseases. We used the 532 complete records after dropping the (mainly missing) data on serum insulin.

Usage

Pima.tr
Pima.tr2
Pima.te

Format

These data frames contains the following columns:

npreg

number of pregnancies.

glu

plasma glucose concentration in an oral glucose tolerance test.

bp

diastolic blood pressure (mm Hg).

skin

triceps skin fold thickness (mm).

bmi

body mass index (weight in kg/(height in m)\^2).

ped

diabetes pedigree function.

age

age in years.

type

Yes or No, for diabetic according to WHO criteria.

Details

The training set Pima.tr contains a randomly selected set of 200 subjects, and Pima.te contains the remaining 332 subjects. Pima.tr2 contains Pima.tr plus 100 subjects with missing values in the explanatory variables.

Source

Smith, J. W., Everhart, J. E., Dickson, W. C., Knowler, W. C. and Johannes, R. S. (1988) Using the ADAP learning algorithm to forecast the onset of diabetes mellitus. In Proceedings of the Symposium on Computer Applications in Medical Care (Washington, 1988), ed. R. A. Greenes, pp. 261–265. Los Alamitos, CA: IEEE Computer Society Press.

Ripley, B.D. (1996) Pattern Recognition and Neural Networks. Cambridge: Cambridge University Press. 

--

Dataset imported from https://www.r-project.org.
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    • Plot - a plot of two columns on the cartesian coordinate system
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    • 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:
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      2. Relative Frequency Histogram
      3. Cumulative Frequency Histogram
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      5. Dotplot
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    • 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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R Output Date
Picostat Output - Arithmetic Mean Jun 10, 2020
Picostat Output - Pie chart Jun 10, 2020
Picostat Output - Pie chart Jun 10, 2020
Picostat Output - Pie chart Jun 10, 2020
Picostat Output - Boxplot Jun 10, 2020
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