The Olson Heart Lung Dataset

Description

We need to determine the effect of the number of revolutions per minute (rpm) of the rotary pump head of an Olson heart-lung pump on the fluid flow rate Liters_minute. The rpm's are replicated at 50, 75, 100, 125, and 150 levels with respective frequencies 5, 3, 5, 2, and 5. The fluid flow rate is measured in litters per minute.

Usage

data(olson)

Format

A data frame with 20 observations on the following 4 variables.

Observation

observation number

rpm

rmp levels at 50, 75, 100, 125, and 150

Level

the rpm levels

Liters_minute

litters per minute

References

Dean, A., and Voss, D. (1999). Design and Analysis of Experiments. Springer.

Examples

data(olson)
par(mfrow=c(2,2))
plot(olson$rpm,olson$Liters_minute,xlim=c(25,175),xlab="RPM",
  ylab="Flow Rate",main="Scatter Plot")
boxplot(Liters_minute~rpm,data=olson,main="Box Plots")
aggregate(olson$Liters_minute,by=list(olson$rpm),mean)
olson_crd <- aov(Liters_minute ~ as.factor(rpm), data=olson)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(ACSWR)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/ACSWR/olson.Rd_%03d_medium.png", width=480, height=480)
> ### Name: olson
> ### Title: The Olson Heart Lung Dataset
> ### Aliases: olson
> ### Keywords: completely randomized design
> 
> ### ** Examples
> 
> data(olson)
> par(mfrow=c(2,2))
> plot(olson$rpm,olson$Liters_minute,xlim=c(25,175),xlab="RPM",
+   ylab="Flow Rate",main="Scatter Plot")
> boxplot(Liters_minute~rpm,data=olson,main="Box Plots")
> aggregate(olson$Liters_minute,by=list(olson$rpm),mean)
  Group.1      x
1      50 1.1352
2      75 1.7220
3     100 2.3268
4     125 2.9250
5     150 3.5292
> olson_crd <- aov(Liters_minute ~ as.factor(rpm), data=olson)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>