oneway.test {stats} | R Documentation |

## Test for Equal Means in a One-Way Layout

### Description

Test whether two or more samples from normal distributions have the
same means. The variances are not necessarily assumed to be equal.

### Usage

oneway.test(formula, data, subset, na.action, var.equal = FALSE)

### Arguments

`formula` |
a formula of the form `lhs ~ rhs` where `lhs`
gives the sample values and `rhs` the corresponding groups. |

`data` |
an optional matrix or data frame (or similar: see
`model.frame` ) containing the variables in the
formula `formula` . By default the variables are taken from
`environment(formula)` . |

`subset` |
an optional vector specifying a subset of observations
to be used. |

`na.action` |
a function which indicates what should happen when
the data contain `NA` s. Defaults to
`getOption("na.action")` . |

`var.equal` |
a logical variable indicating whether to treat the
variances in the samples as equal. If `TRUE` , then a simple F
test for the equality of means in a one-way analysis of variance is
performed. If `FALSE` , an approximate method of Welch (1951)
is used, which generalizes the commonly known 2-sample Welch test to
the case of arbitrarily many samples. |

### Value

A list with class `"htest"`

containing the following components:

`statistic` |
the value of the test statistic. |

`parameter` |
the degrees of freedom of the exact or approximate F
distribution of the test statistic. |

`p.value` |
the p-value of the test. |

`method` |
a character string indicating the test performed. |

`data.name` |
a character string giving the names of the data. |

### References

B. L. Welch (1951),
On the comparison of several mean values: an alternative approach.
*Biometrika*, **38**, 330–336.

### See Also

The standard t test (`t.test`

) as the special case for two
samples;
the Kruskal-Wallis test `kruskal.test`

for a nonparametric
test for equal location parameters in a one-way layout.

### Examples

## Not assuming equal variances
oneway.test(extra ~ group, data = sleep)
## Assuming equal variances
oneway.test(extra ~ group, data = sleep, var.equal = TRUE)
## which gives the same result as
anova(lm(extra ~ group, data = sleep))

[Package

*stats* version 2.5.0

Index]