# oneway.test

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

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

- Keywords
- htest

##### 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.

##### Details

If the right-hand side of the formula contains more than one term, their interaction is taken to form the grouping.

##### 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

`library(stats)`

```
## 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))
```

*Documentation reproduced from package stats, version 3.3, License: Part of R 3.3*

### Community examples

Looks like there are no examples yet.