R Dataset / Package MASS / birthwt

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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Ratio

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Regression

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Stem and Leaf Plots

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Visual Summaries

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Submitted by pmagunia on March 9, 2018 - 1:06 PM
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Attachment Size
dataset-34016.csv 4.84 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 birthwt data set which pertains to Risk Factors Associated with Low Infant Birth Weight. The birthwt data set is found in the MASS R package. Try to load the birthwt data set in R by issuing the following command at the console data("birthwt"). This may load the data into a variable called birthwt. If R says the birthwt 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("birthwt"). 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 birthwt 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 birthwt R data set. The size of this file is about 4,955 bytes.


Risk Factors Associated with Low Infant Birth Weight

Description

The birthwt data frame has 189 rows and 10 columns. The data were collected at Baystate Medical Center, Springfield, Mass during 1986.

Usage

birthwt

Format

This data frame contains the following columns:

low

indicator of birth weight less than 2.5 kg.

age

mother's age in years.

lwt

mother's weight in pounds at last menstrual period.

race

mother's race (1 = white, 2 = black, 3 = other).

smoke

smoking status during pregnancy.

ptl

number of previous premature labours.

ht

history of hypertension.

ui

presence of uterine irritability.

ftv

number of physician visits during the first trimester.

bwt

birth weight in grams.

Source

Hosmer, D.W. and Lemeshow, S. (1989) Applied Logistic Regression. New York: Wiley

References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

Examples

bwt <- with(birthwt, {
race <- factor(race, labels = c("white", "black", "other"))
ptd <- factor(ptl > 0)
ftv <- factor(ftv)
levels(ftv)[-(1:2)] <- "2+"
data.frame(low = factor(low), age, lwt, race, smoke = (smoke > 0),
           ptd, ht = (ht > 0), ui = (ui > 0), ftv)
})
options(contrasts = c("contr.treatment", "contr.poly"))
glm(low ~ ., binomial, bwt)

--

Dataset imported from https://www.r-project.org.
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Picostat Output - Numerical Summaries Dec 27, 2022
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