`R/BSDA-package.R`

`Engineer.Rd`

Data for Example 10.7

`Engineer`

A data frame/tibble with 51 observations on two variables

- salary
salary (in $1000) 10 years after graduation

- university
a factor with levels

`A`

,`B`

, and`C`

Kitchens, L. J. (2003) *Basic Statistics and Data Analysis*.
Pacific Grove, CA: Brooks/Cole, a division of Thomson Learning.

```
boxplot(salary ~ university, data = Engineer,
main = "Example 10.7", col = "yellow")
kruskal.test(salary ~ university, data = Engineer)
#>
#> Kruskal-Wallis rank sum test
#>
#> data: salary by university
#> Kruskal-Wallis chi-squared = 6.3994, df = 2, p-value = 0.04077
#>
anova(lm(salary ~ university, data = Engineer))
#> Analysis of Variance Table
#>
#> Response: salary
#> Df Sum Sq Mean Sq F value Pr(>F)
#> university 2 735.2 367.61 1.5272 0.2275
#> Residuals 48 11553.8 240.70
anova(lm(rank(salary) ~ university, data = Engineer))
#> Analysis of Variance Table
#>
#> Response: rank(salary)
#> Df Sum Sq Mean Sq F value Pr(>F)
#> university 2 1412.7 706.34 3.5226 0.03737 *
#> Residuals 48 9624.8 200.52
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
```