One way analysis of variance

owanova(data, x, y, ...)

Arguments

data
a data frame
x
character vector; name of a continuous variable from data
y
character vector; name of a categorical variable from data
...
additional arguments passed to or from other methods

Value

owanova returns an object of class "owanova". An object of class "owanova" is a list containing the following components:

References

Kutner, M. H., Nachtsheim, C., Neter, J., & Li, W. (2005). Applied linear statistical models. Boston: McGraw-Hill Irwin.

See also

anova

Examples

owanova(mtcars, 'mpg', 'cyl')
#> ANOVA #> -------------------------------------------------------------------- #> Sum of #> Squares DF Mean Square F Sig. #> -------------------------------------------------------------------- #> Between Groups 824.785 2 412.392 39.699 0.0000 #> Within Groups 301.263 29 10.388 #> Total 1126.048 31 #> -------------------------------------------------------------------- #> #> Report #> ---------------------------------------- #> Category N Mean Std. Dev. #> ---------------------------------------- #> 4 11 26.664 4.510 #> 6 7 19.743 1.454 #> 8 14 15.100 2.560 #> ---------------------------------------- #> #> Number of obs = 32 R-squared = 0.7325 #> Root MSE = 3.2231 Adj R-squared = 0.714 #>
owanova(hsb, 'write', 'prog')
#> ANOVA #> ---------------------------------------------------------------------- #> Sum of #> Squares DF Mean Square F Sig. #> ---------------------------------------------------------------------- #> Between Groups 3175.698 2 1587.849 21.275 0.0000 #> Within Groups 14703.177 197 74.635 #> Total 17878.875 199 #> ---------------------------------------------------------------------- #> #> Report #> ----------------------------------------- #> Category N Mean Std. Dev. #> ----------------------------------------- #> 1 45 51.333 9.398 #> 2 105 56.257 7.943 #> 3 50 46.760 9.319 #> ----------------------------------------- #> #> Number of obs = 200 R-squared = 0.1776 #> Root MSE = 8.6392 Adj R-squared = 0.1693 #>