stackloss {datasets} | R Documentation |

## Brownlee's Stack Loss Plant Data

### Description

Operational data of a plant for the oxidation of ammonia to nitric acid.

### Usage

```
stackloss
stack.x
stack.loss
```

### Format

`stackloss`

is a data frame with 21 observations on 4 variables.

[,1] | `Air Flow` | Flow of cooling air |

[,2] | `Water Temp` | Cooling Water Inlet Temperature |

[,3] | `Acid Conc.` | Concentration of acid [per 1000, minus 500] |

[,4] | `stack.loss` | Stack loss |

For historical compatibility with S-PLUS, the data sets
`stack.x`

, a matrix with the first three (independent) variables
of the data frame, and `stack.loss`

, the numeric vector giving
the fourth (dependent) variable, are also provided.

### Details

“Obtained from 21 days of operation of a plant for the
oxidation of ammonia (NH`_3`

) to nitric acid
(HNO`_3`

). The nitric oxides produced are absorbed in a
countercurrent absorption tower”.
(Brownlee, cited by Dodge, slightly reformatted by MM.)

`Air Flow`

represents the rate of operation of the plant.
`Water Temp`

is the temperature of cooling water circulated
through coils in the absorption tower.
`Acid Conc.`

is the concentration of the acid circulating, minus
50, times 10: that is, 89 corresponds to 58.9 per cent acid.
`stack.loss`

(the dependent variable) is 10 times the percentage
of the ingoing ammonia to the plant that escapes from the absorption
column unabsorbed; that is, an (inverse) measure of the over-all
efficiency of the plant.

### Source

Brownlee, K. A. (1960, 2nd ed. 1965)
*Statistical Theory and Methodology in Science and Engineering*.
New York: Wiley. pp. 491–500.

### References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988)
*The New S Language*.
Wadsworth & Brooks/Cole.

Dodge, Y. (1996)
The guinea pig of multiple regression. In:
*Robust Statistics, Data Analysis, and Computer Intensive
Methods; In Honor of Peter Huber's 60th Birthday*, 1996,
*Lecture Notes in Statistics* **109**, Springer-Verlag, New York.

### Examples

```
require(stats)
summary(lm.stack <- lm(stack.loss ~ stack.x))
```

*datasets*version 4.4.1 Index]