normtemp: Body temperature and heart rate of 130 health individuals

Description Usage Format Details Source References Examples

Description

A data set used to investigate the claim that “normal” temperature is 98.6 degrees.

Usage

1

Format

A data frame with 130 observations on the following 3 variables.

temperature

normal body temperature

gender

Gender 1 = male, 2 = female

hr

Resting heart rate

Details

Is normal body temperature 98.6 degrees Fahrenheit? This dataset was constructed to match data presented in an are article intending to establish the true value of “normal” body temperature.

Source

This data set was contributed by Allen L. Shoemaker to the Journal of Statistics Education, http://www.amstat.org/publications/jse/datasets/normtemp.txt.

References

Data set is simulated from values contained in Mackowiak, P. A., Wasserman, S. S., and Levine, M. M. (1992), "A Critical Appraisal of 98.6 Degrees F, the Upper Limit of the Normal Body Temperature, and Other Legacies of Carl Reinhold August Wunderlich," Journal of the American Medical Association, 268, 1578-1580.

Examples

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data(normtemp)
hist(normtemp$temperature)
t.test(normtemp$temperature,mu=98.2)
summary(lm(temperature ~ factor(gender), normtemp))

Example output

Loading required package: MASS
Loading required package: HistData
Loading required package: Hmisc
Loading required package: lattice
Loading required package: survival
Loading required package: Formula
Loading required package: ggplot2

Attaching package: 'Hmisc'

The following objects are masked from 'package:base':

    format.pval, round.POSIXt, trunc.POSIXt, units


Attaching package: 'UsingR'

The following object is masked from 'package:survival':

    cancer


	One Sample t-test

data:  normtemp$temperature
t = 0.76559, df = 129, p-value = 0.4453
alternative hypothesis: true mean is not equal to 98.2
95 percent confidence interval:
 98.12200 98.37646
sample estimates:
mean of x 
 98.24923 


Call:
lm(formula = temperature ~ factor(gender), data = normtemp)

Residuals:
     Min       1Q   Median       3Q      Max 
-1.99385 -0.47154  0.00615  0.40615  2.40615 

Coefficients:
                Estimate Std. Error  t value Pr(>|t|)    
(Intercept)     98.10462    0.08949 1096.298   <2e-16 ***
factor(gender)2  0.28923    0.12655    2.285   0.0239 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.7215 on 128 degrees of freedom
Multiple R-squared:  0.03921,	Adjusted R-squared:  0.0317 
F-statistic: 5.223 on 1 and 128 DF,  p-value: 0.02393

UsingR documentation built on May 2, 2018, 1:03 a.m.