Data for Exercise 10.44

Treatments

## Format

A data frame/tibble with 24 observations on two variables

score

score from an experiment

group

factor with levels 1, 2, and 3

## References

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

## Examples


boxplot(score ~ group, data = Treatments, col = "violet")

summary(aov(score ~ group, data = Treatments))
#>             Df Sum Sq Mean Sq F value Pr(>F)
#> group        2  262.7  131.37    4.05 0.0325 *
#> Residuals   21  681.2   32.44
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
summary(lm(score ~ group, data = Treatments))
#>
#> Call:
#> lm(formula = score ~ group, data = Treatments)
#>
#> Residuals:
#>     Min      1Q  Median      3Q     Max
#> -11.125  -2.469  -0.250   3.875   9.875
#>
#> Coefficients:
#>             Estimate Std. Error t value Pr(>|t|)
#> (Intercept)   32.125      2.014  15.953 3.26e-13 ***
#> group2         8.000      2.848   2.809   0.0105 *
#> group3         5.125      2.848   1.800   0.0863 .
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 5.696 on 21 degrees of freedom
#> Multiple R-squared:  0.2783,	Adjusted R-squared:  0.2096
#> F-statistic:  4.05 on 2 and 21 DF,  p-value: 0.03255
#>
anova(lm(score ~ group, data = Treatments))
#> Analysis of Variance Table
#>
#> Response: score
#>           Df Sum Sq Mean Sq F value  Pr(>F)
#> group      2 262.75  131.38  4.0497 0.03255 *
#> Residuals 21 681.25   32.44
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1