R Dataset / Package boot / calcium

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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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Regression

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Embed
<iframe src="https://embed.picostat.com/r-dataset-package-boot-calcium.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-60234.csv 345 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 calcium data set which pertains to Calcium Uptake Data. The calcium data set is found in the boot R package. You can load the calcium data set in R by issuing the following command at the console data("calcium"). This will load the data into a variable called calcium. If R says the calcium 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 calcium R data set. The size of this file is about 345 bytes.

Documentation

Calcium Uptake Data

Description

The calcium data frame has 27 rows and 2 columns.

Howard Grimes from the Botany Department, North Carolina State University, conducted an experiment for biochemical analysis of intracellular storage and transport of calcium across plasma membrane. Cells were suspended in a solution of radioactive calcium for a certain length of time and then the amount of radioactive calcium that was absorbed by the cells was measured. The experiment was repeated independently with 9 different times of suspension each replicated 3 times.

Usage

calcium

Format

This data frame contains the following columns:

time

The time (in minutes) that the cells were suspended in the solution.

cal

The amount of calcium uptake (nmoles/mg).

Source

The data were obtained from

Rawlings, J.O. (1988) Applied Regression Analysis. Wadsworth and Brooks/Cole Statistics/Probability Series.

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.

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